[{"publication":"Current Biology","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"epub_ahead","OA_type":"hybrid","date_published":"2026-01-12T00:00:00Z","date_created":"2026-01-14T12:00:29Z","author":[{"id":"1271b54b-dbcd-11ea-9d1d-d92da838fe2c","full_name":"Calderon Garcia, Juan Sebastian","last_name":"Calderon Garcia","first_name":"Juan Sebastian"},{"first_name":"Giacomo","last_name":"Costalunga","full_name":"Costalunga, Giacomo"},{"first_name":"Tim P","last_name":"Vogels","orcid":"0000-0003-3295-6181","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"},{"first_name":"Daniela","last_name":"Vallentin","full_name":"Vallentin, Daniela"}],"title":"Interplay between syllable duration and pitch during whistle matching in wild nightingales","project":[{"_id":"0aacfa84-070f-11eb-9043-d7eb2c709234","grant_number":"819603","name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","call_identifier":"H2020"}],"abstract":[{"lang":"eng","text":"During complex vocal interactions, different features of acoustic stimuli are integrated to produce appropriate vocal responses,1 such as copying sounds during vocal matching behavior in some animals.2,3,4,5,6,7,8,9,10,11,12 However, little is known about the interplay and possible trade-offs between the different temporal and spectral acoustic features during these vocal exchanges.2,13,14 Nightingales can flexibly match the pitch of their tonal “whistle songs” in real time during counter-singing duels.15,16 Here, we show that the syllable duration of whistle playbacks could alter the song responses of wild nightingales, causing their whistle duration distribution to shift toward the presented stimulus duration. When exposed to whistle playbacks featuring unnatural combinations of pitch and duration, nightingales demonstrate a flexible trade-off between pitch matching and temporal imitation, yet they are constrained by their vocal repertoire. They selectively adapted their vocal responses to approximate these novel stimuli, aligning them with their natural whistle repertoire. We developed a computational model of nightingale whistle-matching behavior that revealed a hierarchical organization of acoustic feature production. During whistle matching, the feature integration process is constrained by the duration of syllables, and pitch matching follows within this temporal framework, forcing a trade-off between the two features. Our findings reveal a complex interplay between the spectral and temporal domains that shapes song-matching behavior."}],"date_updated":"2026-01-20T07:33:32Z","main_file_link":[{"url":"https://doi.org/10.1016/j.cub.2025.12.025","open_access":"1"}],"department":[{"_id":"GradSch"},{"_id":"TiVo"}],"article_type":"original","scopus_import":"1","_id":"20986","article_processing_charge":"Yes (in subscription journal)","oa_version":"Published Version","day":"12","ddc":["570","577"],"quality_controlled":"1","citation":{"chicago":"Calderon Garcia, Juan Sebastian, Giacomo Costalunga, Tim P Vogels, and Daniela Vallentin. “Interplay between Syllable Duration and Pitch during Whistle Matching in Wild Nightingales.” <i>Current Biology</i>. Elsevier, 2026. <a href=\"https://doi.org/10.1016/j.cub.2025.12.025\">https://doi.org/10.1016/j.cub.2025.12.025</a>.","ama":"Calderon Garcia JS, Costalunga G, Vogels TP, Vallentin D. Interplay between syllable duration and pitch during whistle matching in wild nightingales. <i>Current Biology</i>. 2026. doi:<a href=\"https://doi.org/10.1016/j.cub.2025.12.025\">10.1016/j.cub.2025.12.025</a>","apa":"Calderon Garcia, J. S., Costalunga, G., Vogels, T. P., &#38; Vallentin, D. (2026). Interplay between syllable duration and pitch during whistle matching in wild nightingales. <i>Current Biology</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.cub.2025.12.025\">https://doi.org/10.1016/j.cub.2025.12.025</a>","short":"J.S. Calderon Garcia, G. Costalunga, T.P. Vogels, D. Vallentin, Current Biology (2026).","mla":"Calderon Garcia, Juan Sebastian, et al. “Interplay between Syllable Duration and Pitch during Whistle Matching in Wild Nightingales.” <i>Current Biology</i>, Elsevier, 2026, doi:<a href=\"https://doi.org/10.1016/j.cub.2025.12.025\">10.1016/j.cub.2025.12.025</a>.","ieee":"J. S. Calderon Garcia, G. Costalunga, T. P. Vogels, and D. Vallentin, “Interplay between syllable duration and pitch during whistle matching in wild nightingales,” <i>Current Biology</i>. Elsevier, 2026.","ista":"Calderon Garcia JS, Costalunga G, Vogels TP, Vallentin D. 2026. Interplay between syllable duration and pitch during whistle matching in wild nightingales. Current Biology."},"publisher":"Elsevier","language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2026","oa":1,"doi":"10.1016/j.cub.2025.12.025","has_accepted_license":"1","PlanS_conform":"1","month":"01","acknowledgement":"We would like to thank J. Benichov and N. Hein for their help with fieldwork; M. Ramadas for helping with the segmentation analysis; T. Eliav, C. Chintaluri, G. Tkacik, and A. Navas for providing helpful comments to the project and manuscript; and A. Costalunga for the drawings of nightingales. Funding sources: The Joachim Herz Stiftung Add-on Fellowships for Interdisciplinary Life Science, awarded to G.C.; the ERC Consolidator Grant 819603 SYNAPSEEK, awarded to T.P.V.; and DFG Research Unit 5768–532521431, DFG Research Grant-547921981, DFG SFB 1315–327654276, and the ERC Starting Grant 757459 MIDNIGHT, awarded to D.V.","type":"journal_article","OA_place":"publisher","status":"public","ec_funded":1,"publication_identifier":{"eissn":["1879-0445"],"issn":["0960-9822"]}},{"publication_identifier":{"eissn":["2522-5812"]},"status":"public","OA_place":"publisher","volume":8,"type":"journal_article","acknowledgement":"We thank all members of the laboratory of J.d.J.-S. for insightful discussions and comments. We thank S. Perez for technical assistance. This work was made possible by the Paris Brain Institute Diane Barriere Chair in Synaptic Bioenergetics awarded to J.d.J.-S., who is also supported by an ERC Starting Grant (SynaptoEnergy, European Research Council; ERC-StG-852873), 2019 ATIP-Avenir Grant (CNRS, Inserm), a Big Brain Theory Grant (ICM Foundation) and a Kavli Exploratory Award (Kavli Foundation). This work was also supported by an ERC Advanced Grant (EnergyMeMo; ERC-AdG-741550) to T.P. and grants from the Agence Nationale de la Recherche to P.Y.P. (ANR-20-CE92-0047-01), T.P. (ANR-23-CE16-0029-01), A.P. and J.d.J.-S. (ANR-22-CE16-0020) and J.d.J.-S. (ANR-24-CE16-0221). T.P., P.Y.P. and J.d.J.-S. are permanent CNRS researchers. A.P. is a permanent ESPCI associate professor. T.C. was funded by the French Ministry of Research and the Fondation pour la Recherche Médicale. V.R. was funded by the Max Planck Society, the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation grant number 2024-349543 and the NIH Director’s New Innovator Award (DP2 MH140148). A.B.-G. and C.R.-D. received funding from an ERC Starting Grant (HighMemory; ERC-StG-948217), the Ministry of Economy and Competitiveness (PID2021-122795OB-I00) and the Departament d’Economia i Coneixement de la Generalitat de Catalunya (SGR 00022). T.P.V. was funded by the Wellcome Trust and a Royal Society Sir Henry Dale Research Fellowship (WT100000) and a Wellcome Trust Senior Research Fellowship (214316/Z/18/Z). K.G. was supported by the DIM C-BRAINS, funded by the Conseil Régional d’Ile-de-France. The contributions of H.F. and E.R.S. were supported by the Howard Hughes Medical Institute. The PHENO-ICMice animal Core at ICM is supported by two ‘Investissements d’avenir’ (ANR-10- IAIHU-06 and ANR-11-INBS-0011-NeurATRIS) and the Fondation pour la Recherche Médicale.","month":"02","PlanS_conform":"1","has_accepted_license":"1","page":"467-488","doi":"10.1038/s42255-026-01451-w","issue":"2","oa":1,"year":"2026","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"creator":"dernst","success":1,"access_level":"open_access","file_id":"21392","file_name":"2026_NatureMetab_AmrapaliVishwanath.pdf","date_updated":"2026-03-02T15:21:27Z","file_size":5326608,"content_type":"application/pdf","checksum":"365932a599d05bc9ce8a57204e7a1465","relation":"main_file","date_created":"2026-03-02T15:21:27Z"}],"language":[{"iso":"eng"}],"publisher":"Springer Nature","quality_controlled":"1","citation":{"ista":"Amrapali Vishwanath A, Comyn T, Mira RG, Brossier C, Pascual-Caro C, Faour M, Boumendil K, Chintaluri C, Ramon-Duaso C, Fan R, Ghosh K, Farrants H, Berwick J-P, Sivakumar R, Lopez-Manzaneda M, Schreiter ER, Preat T, Vogels TP, Rangaraju V, Busquets-Garcia A, Plaçais P-Y, Pavlowsky A, de Juan-Sanz J. 2026. Mitochondrial Ca2+ efflux controls neuronal metabolism and long-term memory across species. Nature Metabolism. 8(2), 467–488.","ieee":"A. Amrapali Vishwanath <i>et al.</i>, “Mitochondrial Ca2+ efflux controls neuronal metabolism and long-term memory across species,” <i>Nature Metabolism</i>, vol. 8, no. 2. Springer Nature, pp. 467–488, 2026.","short":"A. Amrapali Vishwanath, T. Comyn, R.G. Mira, C. Brossier, C. Pascual-Caro, M. Faour, K. Boumendil, C. Chintaluri, C. Ramon-Duaso, R. Fan, K. Ghosh, H. Farrants, J.-P. Berwick, R. Sivakumar, M. Lopez-Manzaneda, E.R. Schreiter, T. Preat, T.P. Vogels, V. Rangaraju, A. Busquets-Garcia, P.-Y. Plaçais, A. Pavlowsky, J. de Juan-Sanz, Nature Metabolism 8 (2026) 467–488.","mla":"Amrapali Vishwanath, Anjali, et al. “Mitochondrial Ca2+ Efflux Controls Neuronal Metabolism and Long-Term Memory across Species.” <i>Nature Metabolism</i>, vol. 8, no. 2, Springer Nature, 2026, pp. 467–88, doi:<a href=\"https://doi.org/10.1038/s42255-026-01451-w\">10.1038/s42255-026-01451-w</a>.","ama":"Amrapali Vishwanath A, Comyn T, Mira RG, et al. Mitochondrial Ca2+ efflux controls neuronal metabolism and long-term memory across species. <i>Nature Metabolism</i>. 2026;8(2):467-488. doi:<a href=\"https://doi.org/10.1038/s42255-026-01451-w\">10.1038/s42255-026-01451-w</a>","apa":"Amrapali Vishwanath, A., Comyn, T., Mira, R. G., Brossier, C., Pascual-Caro, C., Faour, M., … de Juan-Sanz, J. (2026). Mitochondrial Ca2+ efflux controls neuronal metabolism and long-term memory across species. <i>Nature Metabolism</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s42255-026-01451-w\">https://doi.org/10.1038/s42255-026-01451-w</a>","chicago":"Amrapali Vishwanath, Anjali, Typhaine Comyn, Rodrigo G. Mira, Claire Brossier, Carlos Pascual-Caro, Maya Faour, Kahina Boumendil, et al. “Mitochondrial Ca2+ Efflux Controls Neuronal Metabolism and Long-Term Memory across Species.” <i>Nature Metabolism</i>. Springer Nature, 2026. <a href=\"https://doi.org/10.1038/s42255-026-01451-w\">https://doi.org/10.1038/s42255-026-01451-w</a>."},"ddc":["570"],"day":"11","oa_version":"Published Version","article_processing_charge":"Yes (in subscription journal)","_id":"21378","article_type":"original","scopus_import":"1","department":[{"_id":"TiVo"}],"intvolume":"         8","date_updated":"2026-03-02T15:23:10Z","abstract":[{"text":"From insects to mammals, essential brain functions, such as forming long-term memories (LTMs), increase metabolic activity in stimulated neurons to meet the energetic demand associated with brain activation. However, while impairing neuronal metabolism limits brain performance, whether expanding the metabolic capacity of neurons boosts brain function remains poorly understood. Here, we show that LTM formation of flies and mice can be enhanced by increasing mitochondrial metabolism in central memory circuits. By knocking down the mitochondrial Ca2+ exporter Letm1, we favour Ca2+ retention in the mitochondrial matrix of neurons due to reduction of mitochondrial H+/Ca2+ exchange. The resulting increase in mitochondrial Ca2+ over-activates mitochondrial metabolism in neurons of central memory circuits, leading to improved LTM storage in training paradigms in which wild-type counterparts of both species fail to remember. Our findings unveil an evolutionarily conserved mechanism that controls mitochondrial metabolism in neurons and indicate its involvement in shaping higher brain functions, such as LTM.","lang":"eng"}],"project":[{"grant_number":"214316/Z/18/Z","name":"What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent neuronal networks.","_id":"c084a126-5a5b-11eb-8a69-d75314a70a87"}],"title":"Mitochondrial Ca2+ efflux controls neuronal metabolism and long-term memory across species","author":[{"last_name":"Amrapali Vishwanath","first_name":"Anjali","full_name":"Amrapali Vishwanath, Anjali"},{"first_name":"Typhaine","last_name":"Comyn","full_name":"Comyn, Typhaine"},{"full_name":"Mira, Rodrigo G.","last_name":"Mira","first_name":"Rodrigo G."},{"first_name":"Claire","last_name":"Brossier","full_name":"Brossier, Claire"},{"last_name":"Pascual-Caro","first_name":"Carlos","full_name":"Pascual-Caro, Carlos"},{"last_name":"Faour","first_name":"Maya","full_name":"Faour, Maya"},{"full_name":"Boumendil, Kahina","last_name":"Boumendil","first_name":"Kahina"},{"orcid":"0000-0003-4252-1608","first_name":"Chaitanya","last_name":"Chintaluri","full_name":"Chintaluri, Chaitanya","id":"BA06AFEE-A4BA-11EA-AE5C-14673DDC885E"},{"full_name":"Ramon-Duaso, Carla","first_name":"Carla","last_name":"Ramon-Duaso"},{"full_name":"Fan, Ruolin","first_name":"Ruolin","last_name":"Fan"},{"full_name":"Ghosh, Kishalay","last_name":"Ghosh","first_name":"Kishalay"},{"last_name":"Farrants","first_name":"Helen","full_name":"Farrants, Helen"},{"last_name":"Berwick","first_name":"Jean-Paul","full_name":"Berwick, Jean-Paul"},{"last_name":"Sivakumar","first_name":"Riya","full_name":"Sivakumar, Riya"},{"full_name":"Lopez-Manzaneda, Mario","first_name":"Mario","last_name":"Lopez-Manzaneda"},{"full_name":"Schreiter, Eric R.","last_name":"Schreiter","first_name":"Eric R."},{"full_name":"Preat, Thomas","first_name":"Thomas","last_name":"Preat"},{"last_name":"Vogels","first_name":"Tim P","orcid":"0000-0003-3295-6181","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"},{"full_name":"Rangaraju, Vidhya","first_name":"Vidhya","last_name":"Rangaraju"},{"first_name":"Arnau","last_name":"Busquets-Garcia","full_name":"Busquets-Garcia, Arnau"},{"full_name":"Plaçais, Pierre-Yves","first_name":"Pierre-Yves","last_name":"Plaçais"},{"full_name":"Pavlowsky, Alice","first_name":"Alice","last_name":"Pavlowsky"},{"first_name":"Jaime","last_name":"de Juan-Sanz","full_name":"de Juan-Sanz, Jaime"}],"date_created":"2026-03-02T10:04:49Z","external_id":{"pmid":["41673453"]},"date_published":"2026-02-11T00:00:00Z","OA_type":"hybrid","publication_status":"published","pmid":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Nature Metabolism","file_date_updated":"2026-03-02T15:21:27Z"},{"month":"04","DOAJ_listed":"1","oa":1,"year":"2026","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"file_id":"21795","access_level":"open_access","success":1,"creator":"dernst","date_created":"2026-05-04T12:20:10Z","relation":"main_file","checksum":"0d26cdb5b8d8dec3a911d8261a65cdef","content_type":"application/pdf","file_size":14925958,"date_updated":"2026-05-04T12:20:10Z","file_name":"2026_CellReports_Vijatovic.pdf"}],"language":[{"iso":"eng"}],"has_accepted_license":"1","PlanS_conform":"1","issue":"4","doi":"10.1016/j.celrep.2026.117227","OA_place":"publisher","volume":45,"publication_identifier":{"issn":["2639-1856"],"eissn":["2211-1247"]},"status":"public","acknowledgement":"We would like to thank the members of the Sweeney Lab, Mario de Bono, Michael Forsthofer, Katharina Lust, and Meital Oren, for comments on the manuscript. We are also grateful to Tom Jessell and Chris Kintner for their scientific insight and mentorship during the conception of this project. It would also have not been possible without the technical support of the Aquatics and Imaging and Optics Facility support teams (ISTA). We thank Martin Estermann for preparing the initial draft of the graphical abstract and Niki Barolini for the final version. In addition, we thank our funding sources for providing the resources to do these experiments: GFF NÖ FTI Strategy Lower Austria dissertation grant FT121-D-046 (to D.V.), Horizon Europe ERC starting grant 101041551 (to Y.I., L.B.S., F.A.T., and D.V.), Special Research Program (SFB) of the Austrian Science Fund (FWF) project F7814-B (to L.B.S.), Austrian Science Fund (FWF) 10.55776/COE16 (to Y.I. and L.B.S.), NINDS 5R35NS116858 (to J.S.D.), CZI grant DAF2020-225401 (DOI) 10.37921/120055ratwvi (to R.H.), NIH grant R01NS123116 (to J.B.B.), American Lebanese Syrian Associated Charities (ALSAC) (to J.B.B.), German Academic Exchange Service (DAAD) IFI grant 57515251-91853472 (to Z.H.), and Project A.L.S. (to S.B.-M.).","type":"journal_article","project":[{"_id":"ebb66355-77a9-11ec-83b8-b8ac210a4dae","grant_number":"101041551","name":"Development and Evolution of Tetrapod Motor Circuits"},{"_id":"8da85f50-16d5-11f0-9cad-eab8b0ff6c9e","grant_number":"F7814","name":"Stem Cell Modulation in Neural Development and Regeneration/ P14-Swim-to-limb transition: cell type to connection diversity"},{"name":"Tools for automation and feedback microscopy","grant_number":"CZI01","_id":"c08e9ad1-5a5b-11eb-8a69-9d1cf3b07473"},{"name":"Development of V1 interneuron diversity during swim-to-walk transition of Xenopus metamorphosis","grant_number":"FTI21-D-046","_id":"bd73af52-d553-11ed-ba76-912049f0ac7a"}],"title":"Multifold increase in spinal inhibitory cell types with emergence of limb movement","author":[{"last_name":"Vijatovic","first_name":"David","id":"cf391e77-ec3c-11ea-a124-d69323410b58","full_name":"Vijatovic, David"},{"first_name":"Florina Alexandra ","last_name":"Toma","id":"2f73f876-f128-11eb-9611-b96b5a30cb0e","full_name":"Toma, Florina Alexandra "},{"last_name":"Ignatyev","first_name":"Y","full_name":"Ignatyev, Y"},{"last_name":"Harrington","first_name":"Zoe P","orcid":"0009-0008-0158-4032","id":"a8144562-32c9-11ee-b5ce-d9800628bda2","full_name":"Harrington, Zoe P"},{"last_name":"Sommer","first_name":"Christoph M","orcid":"0000-0003-1216-9105","full_name":"Sommer, Christoph M","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Hauschild, Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9843-3522","last_name":"Hauschild","first_name":"Robert"},{"last_name":"Smits","first_name":"Matthijs Geert","full_name":"Smits, Matthijs Geert","id":"7a231d52-e216-11ee-a0bb-8acd55f8f1f0"},{"first_name":"Marco","last_name":"Dalla Vecchia","id":"02a7a869-ff06-11ed-a87f-86649d6077e5","full_name":"Dalla Vecchia, Marco"},{"full_name":"Trevisan, Alexandra J.","first_name":"Alexandra J.","last_name":"Trevisan"},{"first_name":"Phillip","last_name":"Chapman","full_name":"Chapman, Phillip"},{"first_name":"Mara","last_name":"Julseth","id":"1cf464b2-dc7d-11ea-9b2f-f9b1aa9417d1","full_name":"Julseth, Mara"},{"full_name":"Brenner-Morton, Susan","first_name":"Susan","last_name":"Brenner-Morton"},{"full_name":"Gabitto, Mariano I.","first_name":"Mariano I.","last_name":"Gabitto"},{"full_name":"Dasen, Jeremy S.","first_name":"Jeremy S.","last_name":"Dasen"},{"first_name":"Jay B.","last_name":"Bikoff","full_name":"Bikoff, Jay B."},{"orcid":"0000-0001-9242-5601","first_name":"Lora Beatrice Jaeger","last_name":"Sweeney","full_name":"Sweeney, Lora Beatrice Jaeger","id":"56BE8254-C4F0-11E9-8E45-0B23E6697425"}],"external_id":{"pmid":["41964955 "]},"date_created":"2026-04-19T22:07:43Z","date_updated":"2026-05-04T12:27:06Z","abstract":[{"text":"As vertebrates transitioned from water to land, locomotion shifted from undulatory swimming to limb-based movement. How spinal circuits and their cell types evolved to support this transition remains unclear. We leverage frog metamorphosis, which recapitulates this transition within a single organism, to define how spinal circuits generate aquatic versus terrestrial motor patterns. At swim stages, spinal architecture is uniform, with a transcriptionally and anatomically homogeneous motor and interneurons. As limbs develop and their movement complexifies, spinal circuits expand in neuron number and subtype diversity. This expansion is most pronounced for V1 inhibitory neurons, which increase ∼70-fold and diversify into transcriptionally distinct subtypes. Disrupting transcription factors defining emerging motor and V1 populations reveals molecular segregation between swim and limb circuits, highlighting the role of subtype diversity in motor coordination. A multifold increase in inhibitory neuron diversity thus underlies the tail-to-limb locomotor transition, providing a framework for spinal circuit adaptation during vertebrate evolution.","lang":"eng"}],"publication_status":"published","pmid":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2026-05-04T12:20:10Z","publication":"Cell Reports","date_published":"2026-04-28T00:00:00Z","OA_type":"gold","corr_author":"1","article_number":"117227","quality_controlled":"1","citation":{"chicago":"Vijatovic, David, Florina Alexandra  Toma, Y Ignatyev, Zoe P Harrington, Christoph M Sommer, Robert Hauschild, Matthijs Geert Smits, et al. “Multifold Increase in Spinal Inhibitory Cell Types with Emergence of Limb Movement.” <i>Cell Reports</i>. Elsevier, 2026. <a href=\"https://doi.org/10.1016/j.celrep.2026.117227\">https://doi.org/10.1016/j.celrep.2026.117227</a>.","apa":"Vijatovic, D., Toma, F. A., Ignatyev, Y., Harrington, Z. P., Sommer, C. M., Hauschild, R., … Sweeney, L. B. (2026). Multifold increase in spinal inhibitory cell types with emergence of limb movement. <i>Cell Reports</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.celrep.2026.117227\">https://doi.org/10.1016/j.celrep.2026.117227</a>","ama":"Vijatovic D, Toma FA, Ignatyev Y, et al. Multifold increase in spinal inhibitory cell types with emergence of limb movement. <i>Cell Reports</i>. 2026;45(4). doi:<a href=\"https://doi.org/10.1016/j.celrep.2026.117227\">10.1016/j.celrep.2026.117227</a>","ieee":"D. Vijatovic <i>et al.</i>, “Multifold increase in spinal inhibitory cell types with emergence of limb movement,” <i>Cell Reports</i>, vol. 45, no. 4. Elsevier, 2026.","short":"D. Vijatovic, F.A. Toma, Y. Ignatyev, Z.P. Harrington, C.M. Sommer, R. Hauschild, M.G. Smits, M. Dalla Vecchia, A.J. Trevisan, P. Chapman, M. Julseth, S. Brenner-Morton, M.I. Gabitto, J.S. Dasen, J.B. Bikoff, L.B. Sweeney, Cell Reports 45 (2026).","mla":"Vijatovic, David, et al. “Multifold Increase in Spinal Inhibitory Cell Types with Emergence of Limb Movement.” <i>Cell Reports</i>, vol. 45, no. 4, 117227, Elsevier, 2026, doi:<a href=\"https://doi.org/10.1016/j.celrep.2026.117227\">10.1016/j.celrep.2026.117227</a>.","ista":"Vijatovic D, Toma FA, Ignatyev Y, Harrington ZP, Sommer CM, Hauschild R, Smits MG, Dalla Vecchia M, Trevisan AJ, Chapman P, Julseth M, Brenner-Morton S, Gabitto MI, Dasen JS, Bikoff JB, Sweeney LB. 2026. Multifold increase in spinal inhibitory cell types with emergence of limb movement. Cell Reports. 45(4), 117227."},"ddc":["570"],"acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"}],"publisher":"Elsevier","article_type":"original","scopus_import":"1","department":[{"_id":"LoSw"},{"_id":"GradSch"},{"_id":"TiVo"},{"_id":"Bio"},{"_id":"NiBa"}],"intvolume":"        45","day":"28","article_processing_charge":"Yes","oa_version":"Published Version","_id":"21746"},{"OA_place":"publisher","volume":17,"status":"public","publication_identifier":{"eissn":["2041-1723"]},"acknowledgement":"We would like to thank Chamith Halahakoon, Phil Cowen, Angharad De Cates, Beata Godlewska, Riccardo De Giorgi, Katherine Smith and Edoardo Ostinelli for enabling this study by providing medical cover. We would like to thank Douglas F. Tomé and Everton J. Agnes for their guidance and advice with earlier versions of the neural network model. We would like to thank Rob Froemke for helpful discussion when preparing the experiments. We thank Leonie Glitz and Valentina Mancini for comments on an earlier version of the manuscript. R.S.K. was supported by an EPSRC/MRC-funded studentship (EP/L016052/1). P.P. was supported by the Cambridge Trust, Trinity Henry Barlow Scholarship and Trinity Hall Brockhouse Scholarship. L.C. is supported by the Foundation for Science and Technology (FCT) (Portuguese State Budget: UID/PSI/01662/2020; Research fellowship: 2021.00415.CEECIND). W.T.C. is funded by the Wellcome Trust [225924/Z/22/Z]. H.C.B. is supported by a UKRI Future Leaders Fellowship (MR/W008939/1) and the Wellcome Institutional Strategic Support Fund. H.C.B. and J.X.O. are supported by the Medical Research Council (MR/W01971X/1). The study was supported by the NIHR Oxford Health Biomedical Research Centre (NIHR203316). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z and 203139/A/16/Z). This research was funded in part by the Wellcome Trust. For the purpose of open access, the author(s) have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.","type":"journal_article","month":"05","DOAJ_listed":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"language":[{"iso":"eng"}],"file":[{"file_size":2059139,"content_type":"application/pdf","checksum":"1b529e06b1c5d6e085d60743317fd4f9","file_name":"2026_NatureComm_Koolschijn.pdf","date_updated":"2026-05-21T07:01:35Z","relation":"main_file","date_created":"2026-05-21T07:01:35Z","success":1,"creator":"dernst","access_level":"open_access","file_id":"21905"}],"oa":1,"year":"2026","PlanS_conform":"1","has_accepted_license":"1","doi":"10.1038/s41467-026-70659-x","ddc":["570"],"quality_controlled":"1","citation":{"mla":"Koolschijn, Renée S., et al. “Noradrenaline Causes a Spread of Association in the Hippocampal Cognitive Map.” <i>Nature Communications</i>, vol. 17, 3961, Springer Nature, 2026, doi:<a href=\"https://doi.org/10.1038/s41467-026-70659-x\">10.1038/s41467-026-70659-x</a>.","short":"R.S. Koolschijn, P. Parthasarathy, M. Browning, X. Przygodda, L.P. Capitão, W.T. Clarke, T.P. Vogels, J.X. O’Reilly, H.C. Barron, Nature Communications 17 (2026).","ieee":"R. S. Koolschijn <i>et al.</i>, “Noradrenaline causes a spread of association in the hippocampal cognitive map,” <i>Nature Communications</i>, vol. 17. Springer Nature, 2026.","ista":"Koolschijn RS, Parthasarathy P, Browning M, Przygodda X, Capitão LP, Clarke WT, Vogels TP, O’Reilly JX, Barron HC. 2026. Noradrenaline causes a spread of association in the hippocampal cognitive map. Nature Communications. 17, 3961.","chicago":"Koolschijn, Renée S., Prakriti Parthasarathy, Michael Browning, Xenia Przygodda, Liliana P. Capitão, William T. Clarke, Tim P Vogels, Jill X. O’Reilly, and Helen C. Barron. “Noradrenaline Causes a Spread of Association in the Hippocampal Cognitive Map.” <i>Nature Communications</i>. Springer Nature, 2026. <a href=\"https://doi.org/10.1038/s41467-026-70659-x\">https://doi.org/10.1038/s41467-026-70659-x</a>.","apa":"Koolschijn, R. S., Parthasarathy, P., Browning, M., Przygodda, X., Capitão, L. P., Clarke, W. T., … Barron, H. C. (2026). Noradrenaline causes a spread of association in the hippocampal cognitive map. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-026-70659-x\">https://doi.org/10.1038/s41467-026-70659-x</a>","ama":"Koolschijn RS, Parthasarathy P, Browning M, et al. Noradrenaline causes a spread of association in the hippocampal cognitive map. <i>Nature Communications</i>. 2026;17. doi:<a href=\"https://doi.org/10.1038/s41467-026-70659-x\">10.1038/s41467-026-70659-x</a>"},"publisher":"Springer Nature","department":[{"_id":"TiVo"}],"intvolume":"        17","scopus_import":"1","article_type":"original","article_processing_charge":"Yes","oa_version":"Published Version","_id":"21895","day":"01","title":"Noradrenaline causes a spread of association in the hippocampal cognitive map","author":[{"first_name":"Renée S.","last_name":"Koolschijn","full_name":"Koolschijn, Renée S."},{"first_name":"Prakriti","last_name":"Parthasarathy","full_name":"Parthasarathy, Prakriti"},{"full_name":"Browning, Michael","first_name":"Michael","last_name":"Browning"},{"last_name":"Przygodda","first_name":"Xenia","full_name":"Przygodda, Xenia"},{"last_name":"Capitão","first_name":"Liliana P.","full_name":"Capitão, Liliana P."},{"last_name":"Clarke","first_name":"William T.","full_name":"Clarke, William T."},{"id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","full_name":"Vogels, Tim P","orcid":"0000-0003-3295-6181","last_name":"Vogels","first_name":"Tim P"},{"last_name":"O’Reilly","first_name":"Jill X.","full_name":"O’Reilly, Jill X."},{"first_name":"Helen C.","last_name":"Barron","full_name":"Barron, Helen C."}],"external_id":{"pmid":["41832186"]},"date_created":"2026-05-20T14:30:37Z","abstract":[{"lang":"eng","text":"The mammalian brain organises knowledge about entities in the world and relationships between them using cognitive maps. When forming a cognitive map, there is a necessary trade-off between extending the map to make novel inferences, and storing a veridical copy of past experience. However, the neural mechanisms that control this trade-off remain unknown. Using a cross-scale approach that combines a pharmacological intervention in humans with neural network modelling, we show that the neuromodulator noradrenaline elicits a significant ‘spread of association’ across hippocampal cognitive maps. This neural spread of association can be explained by changes in synaptic plasticity that predict overgeneralisation in behaviour. Thus, elevated noradrenaline during learning increases the ‘smoothing kernel’ for plasticity across the cognitive map, allowing disparate memories to become linked and distorted."}],"date_updated":"2026-05-21T07:05:01Z","publication":"Nature Communications","file_date_updated":"2026-05-21T07:01:35Z","pmid":1,"publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"3961","date_published":"2026-05-01T00:00:00Z","OA_type":"gold"},{"article_number":"106966","corr_author":"1","OA_type":"gold","date_published":"2025-08-01T00:00:00Z","file_date_updated":"2025-12-30T08:35:41Z","publication":"Neurobiology of Disease","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","abstract":[{"lang":"eng","text":"Status epilepticus (SE), seizures lasting beyond five minutes, is a medical emergency commonly treated with benzodiazepines which enhance GABAA receptor (GABAAR) conductance. Despite widespread use, benzodiazepines fail in over one-third of patients, potentially due to seizure-induced disruption of neuronal chloride (Cl−) homeostasis. Understanding these changes at a network level is crucial for improving clinical translation. Here, we address this using a large-scale spiking neural network model incorporating Cl− dynamics, informed by clinical EEG and experimental slice recordings. Our simulations confirm that the GABAAR reversal potential (EGABA) dictates the pro- or anti-seizure effect of GABAAR conductance modulation, with high EGABA rendering benzodiazepines ineffective or excitatory. We show SE-like activity and EGABA depend non-linearly on Cl− extrusion efficacy and GABAAR conductance. Critically, cell-type specific manipulations reveal that pyramidal cell, not interneuron, Cl− extrusion predominantly determines the severity of SE activity and the response to simulated benzodiazepines. Leveraging these mechanistic insights, we develop a predictive framework mapping network states to Cl− extrusion capacity and GABAergic load, yielding a proposed decision-making strategy to guide therapeutic interventions based on initial treatment response. This work identifies pyramidal cell Cl− handling as a key therapeutic target and demonstrates the utility of biophysically detailed network models for optimising SE treatment protocols."}],"date_updated":"2025-12-30T08:36:36Z","external_id":{"isi":["001501576500001"]},"date_created":"2025-06-08T22:01:22Z","title":"Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus","author":[{"first_name":"Christopher","last_name":"Currin","orcid":"0000-0002-4809-5059","id":"e8321fc5-3091-11eb-8a53-83f309a11ac9","full_name":"Currin, Christopher"},{"first_name":"Richard J.","last_name":"Burman","full_name":"Burman, Richard J."},{"full_name":"Fedele, Tommaso","last_name":"Fedele","first_name":"Tommaso"},{"last_name":"Ramantani","first_name":"Georgia","full_name":"Ramantani, Georgia"},{"full_name":"Rosch, Richard E.","last_name":"Rosch","first_name":"Richard E."},{"full_name":"Sprekeler, Henning","last_name":"Sprekeler","first_name":"Henning"},{"full_name":"Raimondo, Joseph V.","first_name":"Joseph V.","last_name":"Raimondo"}],"_id":"19794","oa_version":"Published Version","article_processing_charge":"Yes","day":"01","intvolume":"       212","department":[{"_id":"TiVo"}],"article_type":"original","scopus_import":"1","publisher":"Elsevier","ddc":["570"],"quality_controlled":"1","citation":{"mla":"Currin, Christopher, et al. “Network Models Incorporating Chloride Dynamics Predict Optimal Strategies for Terminating Status Epilepticus.” <i>Neurobiology of Disease</i>, vol. 212, 106966, Elsevier, 2025, doi:<a href=\"https://doi.org/10.1016/j.nbd.2025.106966\">10.1016/j.nbd.2025.106966</a>.","short":"C. Currin, R.J. Burman, T. Fedele, G. Ramantani, R.E. Rosch, H. Sprekeler, J.V. Raimondo, Neurobiology of Disease 212 (2025).","ieee":"C. Currin <i>et al.</i>, “Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus,” <i>Neurobiology of Disease</i>, vol. 212. Elsevier, 2025.","ista":"Currin C, Burman RJ, Fedele T, Ramantani G, Rosch RE, Sprekeler H, Raimondo JV. 2025. Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus. Neurobiology of Disease. 212, 106966.","chicago":"Currin, Christopher, Richard J. Burman, Tommaso Fedele, Georgia Ramantani, Richard E. Rosch, Henning Sprekeler, and Joseph V. Raimondo. “Network Models Incorporating Chloride Dynamics Predict Optimal Strategies for Terminating Status Epilepticus.” <i>Neurobiology of Disease</i>. Elsevier, 2025. <a href=\"https://doi.org/10.1016/j.nbd.2025.106966\">https://doi.org/10.1016/j.nbd.2025.106966</a>.","ama":"Currin C, Burman RJ, Fedele T, et al. Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus. <i>Neurobiology of Disease</i>. 2025;212. doi:<a href=\"https://doi.org/10.1016/j.nbd.2025.106966\">10.1016/j.nbd.2025.106966</a>","apa":"Currin, C., Burman, R. J., Fedele, T., Ramantani, G., Rosch, R. E., Sprekeler, H., &#38; Raimondo, J. V. (2025). Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus. <i>Neurobiology of Disease</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.nbd.2025.106966\">https://doi.org/10.1016/j.nbd.2025.106966</a>"},"doi":"10.1016/j.nbd.2025.106966","has_accepted_license":"1","file":[{"file_id":"20896","access_level":"open_access","success":1,"creator":"dernst","date_created":"2025-12-30T08:35:41Z","relation":"main_file","file_size":7063352,"checksum":"abe215be676ed14e9a37fb78b6a5a610","content_type":"application/pdf","date_updated":"2025-12-30T08:35:41Z","file_name":"2025_NeurobioDisease_Currin.pdf"}],"language":[{"iso":"eng"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)","short":"CC BY-NC (4.0)","image":"/images/cc_by_nc.png"},"year":"2025","oa":1,"DOAJ_listed":"1","isi":1,"month":"08","type":"journal_article","acknowledgement":"The research leading to these results has received support from the National Research Foundation of South Africa, the Deutscher Akademischer Austauschdienst, NOMIS Foundation, NVIDIA Academic Program, the University of Cape Town, the Anna Mueller Grocholski Foundation, the Swiss National Science Foundation (SNSF: 208184), the Gabriel Foundation, a Wellcome Trust Seed Award (214042/Z/18/Z), the South African Medical Research Council and the FLAIR Fellowship Programme (FLR\\R1\\190829): a partnership between the African Academy of Sciences and the Royal Society funded by the UK Government's Global Challenges Research Fund and a Wellcome Trust International Intermediate Fellowship (222968/Z/21/Z).","status":"public","publication_identifier":{"eissn":["1095-953X"],"issn":["0969-9961"]},"volume":212,"OA_place":"publisher"},{"publication":"Proceedings of the National Academy of Sciences","file_date_updated":"2025-02-17T14:46:18Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","pmid":1,"publication_status":"published","article_number":"e2408966122","OA_type":"hybrid","date_published":"2025-01-22T00:00:00Z","external_id":{"pmid":["39841147"],"isi":["001422380500004"]},"date_created":"2025-02-17T09:20:19Z","title":"Layer-specific control of inhibition by NDNF interneurons","author":[{"full_name":"Naumann, Laura B","id":"81a3b706-8972-11ed-ae7b-8eff728700ca","first_name":"Laura B","last_name":"Naumann"},{"first_name":"Loreen","last_name":"Hertäg","full_name":"Hertäg, Loreen"},{"full_name":"Müller, Jennifer","first_name":"Jennifer","last_name":"Müller"},{"full_name":"Letzkus, Johannes J.","first_name":"Johannes J.","last_name":"Letzkus"},{"full_name":"Sprekeler, Henning","first_name":"Henning","last_name":"Sprekeler"}],"abstract":[{"lang":"eng","text":"Neuronal processing of external sensory input is shaped by internally generated top–down information. In the neocortex, top–down projections primarily target layer 1, which contains NDNF (neuron-derived neurotrophic factor)-expressing interneurons and the dendrites of pyramidal cells. Here, we investigate the hypothesis that NDNF interneurons shape cortical computations in an unconventional, layer-specific way, by exerting presynaptic inhibition on synapses in layer 1 while leaving synapses in deeper layers unaffected. We first confirm experimentally that in the auditory cortex, synapses from somatostatin-expressing (SOM) onto NDNF neurons are indeed modulated by ambient Gamma-aminobutyric acid (GABA). Shifting to a computational model, we then show that this mechanism introduces a distinct mutual inhibition motif between NDNF interneurons and the synaptic outputs of SOM interneurons. This motif can control inhibition in a layer-specific way and introduces competition between NDNF and SOM interneurons for dendritic inhibition onto pyramidal cells on different timescales. NDNF interneurons can thereby control cortical information flow by redistributing dendritic inhibition from fast to slow timescales and by gating different sources of dendritic inhibition."}],"date_updated":"2026-02-16T12:28:02Z","intvolume":"       122","department":[{"_id":"TiVo"}],"scopus_import":"1","article_type":"original","_id":"19036","oa_version":"Published Version","article_processing_charge":"Yes (in subscription journal)","day":"22","ddc":["570"],"quality_controlled":"1","citation":{"chicago":"Naumann, Laura B, Loreen Hertäg, Jennifer Müller, Johannes J. Letzkus, and Henning Sprekeler. “Layer-Specific Control of Inhibition by NDNF Interneurons.” <i>Proceedings of the National Academy of Sciences</i>. National Academy of Sciences, 2025. <a href=\"https://doi.org/10.1073/pnas.2408966122\">https://doi.org/10.1073/pnas.2408966122</a>.","apa":"Naumann, L. B., Hertäg, L., Müller, J., Letzkus, J. J., &#38; Sprekeler, H. (2025). Layer-specific control of inhibition by NDNF interneurons. <i>Proceedings of the National Academy of Sciences</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.2408966122\">https://doi.org/10.1073/pnas.2408966122</a>","ama":"Naumann LB, Hertäg L, Müller J, Letzkus JJ, Sprekeler H. Layer-specific control of inhibition by NDNF interneurons. <i>Proceedings of the National Academy of Sciences</i>. 2025;122(4). doi:<a href=\"https://doi.org/10.1073/pnas.2408966122\">10.1073/pnas.2408966122</a>","short":"L.B. Naumann, L. Hertäg, J. Müller, J.J. Letzkus, H. Sprekeler, Proceedings of the National Academy of Sciences 122 (2025).","mla":"Naumann, Laura B., et al. “Layer-Specific Control of Inhibition by NDNF Interneurons.” <i>Proceedings of the National Academy of Sciences</i>, vol. 122, no. 4, e2408966122, National Academy of Sciences, 2025, doi:<a href=\"https://doi.org/10.1073/pnas.2408966122\">10.1073/pnas.2408966122</a>.","ieee":"L. B. Naumann, L. Hertäg, J. Müller, J. J. Letzkus, and H. Sprekeler, “Layer-specific control of inhibition by NDNF interneurons,” <i>Proceedings of the National Academy of Sciences</i>, vol. 122, no. 4. National Academy of Sciences, 2025.","ista":"Naumann LB, Hertäg L, Müller J, Letzkus JJ, Sprekeler H. 2025. Layer-specific control of inhibition by NDNF interneurons. Proceedings of the National Academy of Sciences. 122(4), e2408966122."},"publisher":"National Academy of Sciences","file":[{"relation":"main_file","date_created":"2025-02-17T14:46:18Z","checksum":"636d5130724e3236ebf4fc658b3945fe","file_size":13726531,"content_type":"application/pdf","file_name":"2025_PNAS_Naumann.pdf","date_updated":"2025-02-17T14:46:18Z","file_id":"19046","success":1,"creator":"dernst","access_level":"open_access"}],"language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"year":"2025","oa":1,"doi":"10.1073/pnas.2408966122","issue":"4","related_material":{"link":[{"relation":"software","url":"https://github.com/LNaumann/NDNF_control_inhibition_Naumann25"}]},"has_accepted_license":"1","month":"01","isi":1,"acknowledgement":"We thank all members of the Letzkus lab, the Sprekeler lab, and the Vogels lab for discussions, U. Thirimanna for technical assistance, and K. Deisseroth for generously sharing reagents. This work was supported by the German Research Foundation (LE 3804/3-1, LE 3804/4-1, LE 3804/7-1, CRC-TRR 384/1 2024, - 514483642, and 460088091) and the Wellcome Trust Senior Research Fellowship 214316/Z/18/Z.\r\nElectrophysiological recordings, source code for simulations, and data analysis have been deposited in GitHub (https://github.com/LNaumann/NDNF_control_inhibition_Naumann25) (62).","type":"journal_article","volume":122,"OA_place":"publisher","status":"public","publication_identifier":{"issn":["0027-8424"],"eissn":["1091-6490"]}},{"DOAJ_listed":"1","month":"02","doi":"10.1016/j.rinam.2025.100548","related_material":{"link":[{"url":"https://doi.org/10.6084/m9.figshare.24081849","relation":"software"}]},"has_accepted_license":"1","language":[{"iso":"eng"}],"file":[{"file_id":"19083","access_level":"open_access","creator":"dernst","success":1,"date_created":"2025-02-24T13:18:47Z","relation":"main_file","date_updated":"2025-02-24T13:18:47Z","file_name":"2025_ResultsApplMath_Paraskevov.pdf","content_type":"application/pdf","checksum":"58fd02e951857859f39d06661a27bcc9","file_size":853322}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2025","oa":1,"status":"public","ec_funded":1,"publication_identifier":{"eissn":["2590-0374"]},"volume":25,"OA_place":"publisher","type":"journal_article","acknowledgement":"The author thanks T.S. Zemskova and N.D. Efimova for verifying some of the results. This work was supported by a European Research Council Consolidator Grant (SYNAPSEEK, 819603, to Tim P. Vogels).\r\nThe Supplementary Material for this article contains (i) the data for graphs in Figure 1 and (ii) ready-to-use MATLAB codes for reproducing the data. It is available online at https://doi.org/10.6084/m9.figshare.24081849.","abstract":[{"text":"Whether or not the neuron emits a spike in response to stimulation by an excitatory current pulse is determined by a strength-duration curve (SDC) for the pulse parameters. The SDC is a dependence of the minimal pulse amplitude required to elicit the spiking response on either the pulse duration or its decay time. Excitatory neurons affect the others through pulses of excitatory postsynaptic current. A simple yet plausible approximation for the time course of such a pulse is the alpha function, with linear rise at the start and exponential decay at the end. However, an exact analytical SDC for this case is hitherto not known, even for the leaky integrate-and-fire (LIF) neuron, the simplest spiking neuron model used in practice. We have obtained general SDC equations for the LIF neuron. Using the Lambert W function — a widely-implemented special function, we have found the exact analytical SDC for the spiking response of the LIF neuron stimulated by an excitatory current pulse in the form of the alpha function. To compare results in a unified way, we have also derived the analytical SDCs for (i) rectangular pulse, (ii) ascending ramp pulse, and (iii) instantly rising and exponentially decaying pulse. In the limit of no leakage, we show that the SDC is reduced to the classical hyperbola for all considered cases.","lang":"eng"}],"date_updated":"2025-04-14T07:54:31Z","date_created":"2025-02-23T23:01:55Z","title":"Analytical strength-duration curve for the spiking response of the LIF neuron to an alpha-function-shaped excitatory current pulse","author":[{"last_name":"Paraskevov","first_name":"Alexander","id":"d05e3c56-9262-11ed-9231-be692464e5ac","full_name":"Paraskevov, Alexander"}],"project":[{"name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","grant_number":"819603","call_identifier":"H2020","_id":"0aacfa84-070f-11eb-9043-d7eb2c709234"}],"article_number":"100548","corr_author":"1","OA_type":"gold","date_published":"2025-02-01T00:00:00Z","publication":"Results in Applied Mathematics","file_date_updated":"2025-02-24T13:18:47Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","publisher":"Elsevier","ddc":["570","510"],"citation":{"ista":"Paraskevov A. 2025. Analytical strength-duration curve for the spiking response of the LIF neuron to an alpha-function-shaped excitatory current pulse. Results in Applied Mathematics. 25, 100548.","short":"A. Paraskevov, Results in Applied Mathematics 25 (2025).","mla":"Paraskevov, Alexander. “Analytical Strength-Duration Curve for the Spiking Response of the LIF Neuron to an Alpha-Function-Shaped Excitatory Current Pulse.” <i>Results in Applied Mathematics</i>, vol. 25, 100548, Elsevier, 2025, doi:<a href=\"https://doi.org/10.1016/j.rinam.2025.100548\">10.1016/j.rinam.2025.100548</a>.","ieee":"A. Paraskevov, “Analytical strength-duration curve for the spiking response of the LIF neuron to an alpha-function-shaped excitatory current pulse,” <i>Results in Applied Mathematics</i>, vol. 25. Elsevier, 2025.","apa":"Paraskevov, A. (2025). Analytical strength-duration curve for the spiking response of the LIF neuron to an alpha-function-shaped excitatory current pulse. <i>Results in Applied Mathematics</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.rinam.2025.100548\">https://doi.org/10.1016/j.rinam.2025.100548</a>","ama":"Paraskevov A. Analytical strength-duration curve for the spiking response of the LIF neuron to an alpha-function-shaped excitatory current pulse. <i>Results in Applied Mathematics</i>. 2025;25. doi:<a href=\"https://doi.org/10.1016/j.rinam.2025.100548\">10.1016/j.rinam.2025.100548</a>","chicago":"Paraskevov, Alexander. “Analytical Strength-Duration Curve for the Spiking Response of the LIF Neuron to an Alpha-Function-Shaped Excitatory Current Pulse.” <i>Results in Applied Mathematics</i>. Elsevier, 2025. <a href=\"https://doi.org/10.1016/j.rinam.2025.100548\">https://doi.org/10.1016/j.rinam.2025.100548</a>."},"_id":"19068","article_processing_charge":"Yes","oa_version":"Published Version","day":"01","intvolume":"        25","department":[{"_id":"TiVo"}],"article_type":"original","scopus_import":"1"},{"date_updated":"2026-04-07T12:36:08Z","abstract":[{"text":"Left–right alternation is a defining feature of spinal locomotor circuits, yet the level of neuronal\r\ndetail required to generate and maintain this pattern remains unclear. This thesis investigates how\r\nmodels spanning multiple levels of abstraction—from biophysically detailed Hodgkin–Huxley (HH)\r\nneurons to adaptive integrate–and–fire (I&F) formulations and synfire-chain modules—can account\r\nfor the generation of fictive swimming in the spinal cord of the Xenopus laevis tadpole. The guiding\r\nhypothesis is that a small set of neuronal mechanisms is sufficient to reproduce the essential features\r\nof rhythmic alternation, and that moving between modeling scales helps distinguish core principles\r\nfrom biological detail.\r\nA minimal bilateral HH network comprising only four canonical neuron classes—excitatory\r\ndescending interneurons (dINs), inhibitory commissural interneurons (cINs), ipsilateral inhibitory\r\ninterneurons (aINs) and motoneurons—served as a biophysical proof of concept. Tuned to reproduce\r\nexperimentally observed firing modes, the model demonstrated that rebound-prone dIN excitability,\r\ncontralateral inhibition and modest electrical coupling are sufficient to generate stable alternating\r\nactivity, even in very small networks. These results motivated the transition to simpler models\r\ncapable of efficient analysis and scaling.\r\nAdaptive exponential I&F (AdEx) neurons were calibrated to physiological recordings using\r\nsimulation-based inference, yielding tonic and phasic/rebound templates that preserved the key\r\ndynamical signatures of the HH model. Phase-plane analysis clarified the mechanisms underlying\r\nsingle-spike responses and rebound firing in dINs. At network level, the I&F models robustly\r\nreproduced left–right alternation, while highlighting constraints on synaptic kinetics and adaptation\r\nneeded to avoid multi-spike responses.\r\nFinally, a synfire-chain framework provided a complementary, timing-centric perspective, demonstrating how precise spike synchrony, synaptic delays and minimal inhibitory coupling can generate\r\nalternating left–right sequences in a feedforward setting. Together, these approaches converge on a\r\ncommon conclusion: rebound-prone ipsilateral excitation combined with precisely timed contralateral inhibition constitutes a sufficient substrate for alternating spinal rhythms.\r\nBy integrating bottom-up and top-down modeling strategies, this thesis provides a unified, extensible framework for studying spinal pattern generation. The results show that essential locomotor\r\ndynamics can be captured across multiple abstraction levels, offering both mechanistic insight and\r\npractical tools for future data-driven investigations of spinal circuit development, robustness and\r\nmodulation.","lang":"eng"}],"date_created":"2025-12-08T09:49:41Z","title":"Modelling the spinal cord of a tadpole : Exploring different ways to model the spinal cord in the Xenopus frog","author":[{"full_name":"Wilson, Alexia C","id":"5230e794-15b2-11ec-abd3-e2d5335ebd1d","orcid":"0000-0001-6191-1367","first_name":"Alexia C","last_name":"Wilson"}],"date_published":"2025-12-09T00:00:00Z","corr_author":"1","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","publication_status":"published","file_date_updated":"2026-01-04T12:58:49Z","publisher":"Institute of Science and Technology Austria","citation":{"ieee":"A. C. Wilson, “Modelling the spinal cord of a tadpole : Exploring different ways to model the spinal cord in the Xenopus frog,” Institute of Science and Technology Austria, 2025.","mla":"Wilson, Alexia C. <i>Modelling the Spinal Cord of a Tadpole : Exploring Different Ways to Model the Spinal Cord in the Xenopus Frog</i>. Institute of Science and Technology Austria, 2025, doi:<a href=\"https://doi.org/10.15479/AT-ISTA-20735\">10.15479/AT-ISTA-20735</a>.","short":"A.C. Wilson, Modelling the Spinal Cord of a Tadpole : Exploring Different Ways to Model the Spinal Cord in the Xenopus Frog, Institute of Science and Technology Austria, 2025.","ista":"Wilson AC. 2025. Modelling the spinal cord of a tadpole : Exploring different ways to model the spinal cord in the Xenopus frog. Institute of Science and Technology Austria.","chicago":"Wilson, Alexia C. “Modelling the Spinal Cord of a Tadpole : Exploring Different Ways to Model the Spinal Cord in the Xenopus Frog.” Institute of Science and Technology Austria, 2025. <a href=\"https://doi.org/10.15479/AT-ISTA-20735\">https://doi.org/10.15479/AT-ISTA-20735</a>.","apa":"Wilson, A. C. (2025). <i>Modelling the spinal cord of a tadpole : Exploring different ways to model the spinal cord in the Xenopus frog</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT-ISTA-20735\">https://doi.org/10.15479/AT-ISTA-20735</a>","ama":"Wilson AC. Modelling the spinal cord of a tadpole : Exploring different ways to model the spinal cord in the Xenopus frog. 2025. doi:<a href=\"https://doi.org/10.15479/AT-ISTA-20735\">10.15479/AT-ISTA-20735</a>"},"supervisor":[{"orcid":"0000-0003-3295-6181","last_name":"Vogels","first_name":"Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","full_name":"Vogels, Tim P"},{"full_name":"Sweeney, Lora Beatrice Jaeger","id":"56BE8254-C4F0-11E9-8E45-0B23E6697425","orcid":"0000-0001-9242-5601","last_name":"Sweeney","first_name":"Lora Beatrice Jaeger"}],"ddc":["570","596","005"],"day":"09","_id":"20735","oa_version":"Published Version","article_processing_charge":"No","department":[{"_id":"GradSch"},{"_id":"TiVo"},{"_id":"LoSw"}],"alternative_title":["ISTA Master's Thesis"],"month":"12","doi":"10.15479/AT-ISTA-20735","related_material":{"record":[{"status":"public","id":"13097","relation":"part_of_dissertation"}]},"page":"110","has_accepted_license":"1","year":"2025","oa":1,"file":[{"file_id":"20919","access_level":"closed","creator":"awilson","date_created":"2026-01-01T17:26:30Z","relation":"source_file","checksum":"9e3b6b73f8cbec2c3687d17fe8e30410","content_type":"application/zip","file_size":566072368,"date_updated":"2026-01-02T13:05:07Z","file_name":"tadpoleAdEx.zip"},{"content_type":"application/pdf","file_size":7170097,"checksum":"13f4c0d33923e9d5c9d56731345cf21d","file_name":"Masters_Thesis_Alexia_Wilson_FINAL_pdfA.pdf","date_updated":"2026-01-04T12:58:49Z","date_created":"2026-01-04T12:58:49Z","relation":"main_file","access_level":"open_access","success":1,"creator":"awilson","file_id":"20923"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["2791-4585"]},"status":"public","OA_place":"publisher","type":"dissertation","degree_awarded":"MS"},{"isi":1,"locked":"1","month":"03","related_material":{"link":[{"url":"https://github.com/wpodlaski/contextual-memory-nets","relation":"software"}]},"has_accepted_license":"1","doi":"10.1103/PhysRevX.15.011057","oa":1,"year":"2025","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"language":[{"iso":"eng"}],"file":[{"date_created":"2025-03-20T12:47:17Z","relation":"main_file","checksum":"1f27ee469ab51a3e1ce1e2df0022e81d","content_type":"application/pdf","file_size":1373704,"file_name":"2025_PhysReviewX_Podlaski.pdf","date_updated":"2025-03-20T12:47:17Z","file_id":"19432","access_level":"open_access","success":1,"creator":"dernst"}],"publication_identifier":{"eissn":["2160-3308"]},"status":"public","OA_place":"publisher","volume":15,"type":"journal_article","acknowledgement":"We thank Helen Barron, Vezha Boboeva, Adam Packer, João Sacramento, Andrew Saxe, Misha Tsodyks, and Friedemann Zenke for helpful comments at various stages of this work, and Rubem Erichsen, Jr. for carefully reading the manuscript and valuable comments. This work was\r\nsupported by a Sir Henry Dale Fellowship by the Wellcome Trust and the Royal Society [No. WT100000 (W. F. P., E. J. A., and T. P. V.)], a Wellcome Trust Senior Research Fellowship [No. 214316/Z/18/Z (E. J. A. and T. P. V.)], and a Research Project Grant by the Leverhulme Trust\r\n[No. RPG-2016-446 (E. J. A.)]. ","APC_amount":"4910,08 EUR","date_updated":"2026-05-06T12:44:27Z","abstract":[{"text":"Biological memory is known to be flexible—memory formation and recall depend on factors such as the behavioral context of the organism. However, this property is often ignored in associative memory models, leaving it unclear how memories can be organized and recalled when subject to contextual control. Because of the lack of a rigorous analytical framework, it is also unknown how contextual control affects memory stability, storage capacity, and information content. Here, we bring the dynamic nature of memory to the fore by introducing a novel model of associative memory, which we refer to as the context-modular memory network. In our model, stored memory patterns are associated to one of several background network states, or contexts. Memories are accessible when their corresponding context is active, and are otherwise inaccessible. Context modulates the effective network connectivity by imposing a specific\r\nconfiguration of neuronal and synaptic gating—gated neurons (synapses) have their activity (weights) momentarily silenced, thereby reducing interference from memories belonging to other contexts. Memory patterns are randomly and independently chosen, while neuronal and synaptic gates may be selected randomly or optimized through a process of contextual synaptic refinement. Through analytic and numerical results, we show that context-modular memory networks can exhibit both improved memory capacity and differential control of memory stability with random gating (especially for neuronal gating). For contextual synaptic refinement, we devise a method in which synapses are gated off for a given context if they destabilize the memory patterns in that context, drastically improving memory capacity and enabling even more precise control over memory stability. Notably, synaptic refinement allows for patterns to be\r\naccessible in multiple contexts, stabilizing memory patterns even for weight matrices that alone do not contain any information about the memory patterns, such as Gaussian random matrices. Overall, our model integrates recent ideas about context-dependent memory organization with classic associative memory models and proposes a rigorous theory which can act as a framework for future work. Furthermore, our work carries important implications for the understanding of biological memory storage and recall in the brain, such as highlighting an intriguing trade-off between memory capacity and accessibility.","lang":"eng"}],"project":[{"name":"IST Austria Open Access Fund","_id":"B67AFEDC-15C9-11EA-A837-991A96BB2854"},{"_id":"c084a126-5a5b-11eb-8a69-d75314a70a87","grant_number":"214316/Z/18/Z","name":"What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent neuronal networks."}],"title":"High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating","author":[{"full_name":"Podlaski, William F.","last_name":"Podlaski","first_name":"William F.","orcid":"0000-0001-6619-7502"},{"last_name":"Agnes","first_name":"Everton J.","orcid":"0000-0001-7184-7311","full_name":"Agnes, Everton J."},{"first_name":"Tim P","last_name":"Vogels","orcid":"0000-0003-3295-6181","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","full_name":"Vogels, Tim P"}],"date_created":"2020-07-16T12:24:28Z","external_id":{"isi":["001451378900002"]},"date_published":"2025-03-13T00:00:00Z","OA_type":"gold","corr_author":"1","article_number":"011057","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2025-03-20T12:47:17Z","publication":"Physical Review X","publisher":"American Physical Society","citation":{"ista":"Podlaski WF, Agnes EJ, Vogels TP. 2025. High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating. Physical Review X. 15, 011057.","ieee":"W. F. Podlaski, E. J. Agnes, and T. P. Vogels, “High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating,” <i>Physical Review X</i>, vol. 15. American Physical Society, 2025.","mla":"Podlaski, William F., et al. “High Capacity and Dynamic Accessibility in Associative Memory Networks with Context-Dependent Neuronal and Synaptic Gating.” <i>Physical Review X</i>, vol. 15, 011057, American Physical Society, 2025, doi:<a href=\"https://doi.org/10.1103/PhysRevX.15.011057\">10.1103/PhysRevX.15.011057</a>.","short":"W.F. Podlaski, E.J. Agnes, T.P. Vogels, Physical Review X 15 (2025).","apa":"Podlaski, W. F., Agnes, E. J., &#38; Vogels, T. P. (2025). High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating. <i>Physical Review X</i>. American Physical Society. <a href=\"https://doi.org/10.1103/PhysRevX.15.011057\">https://doi.org/10.1103/PhysRevX.15.011057</a>","ama":"Podlaski WF, Agnes EJ, Vogels TP. High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating. <i>Physical Review X</i>. 2025;15. doi:<a href=\"https://doi.org/10.1103/PhysRevX.15.011057\">10.1103/PhysRevX.15.011057</a>","chicago":"Podlaski, William F., Everton J. Agnes, and Tim P Vogels. “High Capacity and Dynamic Accessibility in Associative Memory Networks with Context-Dependent Neuronal and Synaptic Gating.” <i>Physical Review X</i>. American Physical Society, 2025. <a href=\"https://doi.org/10.1103/PhysRevX.15.011057\">https://doi.org/10.1103/PhysRevX.15.011057</a>."},"quality_controlled":"1","ddc":["530"],"day":"13","oa_version":"Published Version","article_processing_charge":"Yes","_id":"8125","article_type":"original","scopus_import":"1","department":[{"_id":"TiVo"}],"intvolume":"        15"},{"publisher":"Public Library of Science","ddc":["570"],"quality_controlled":"1","citation":{"ista":"Confavreux BJ, Agnes EJ, Zenke F, Sprekeler H, Vogels TP. 2025. Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks. PLoS Computational Biology. 21(4), e1012910.","short":"B.J. Confavreux, E.J. Agnes, F. Zenke, H. Sprekeler, T.P. Vogels, PLoS Computational Biology 21 (2025).","mla":"Confavreux, Basile J., et al. “Balancing Complexity, Performance and Plausibility to Meta Learn Plasticity Rules in Recurrent Spiking Networks.” <i>PLoS Computational Biology</i>, vol. 21, no. 4, e1012910, Public Library of Science, 2025, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1012910\">10.1371/journal.pcbi.1012910</a>.","ieee":"B. J. Confavreux, E. J. Agnes, F. Zenke, H. Sprekeler, and T. P. Vogels, “Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks,” <i>PLoS Computational Biology</i>, vol. 21, no. 4. Public Library of Science, 2025.","ama":"Confavreux BJ, Agnes EJ, Zenke F, Sprekeler H, Vogels TP. Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks. <i>PLoS Computational Biology</i>. 2025;21(4). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1012910\">10.1371/journal.pcbi.1012910</a>","apa":"Confavreux, B. J., Agnes, E. J., Zenke, F., Sprekeler, H., &#38; Vogels, T. P. (2025). Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1012910\">https://doi.org/10.1371/journal.pcbi.1012910</a>","chicago":"Confavreux, Basile J, Everton J. Agnes, Friedemann Zenke, Henning Sprekeler, and Tim P Vogels. “Balancing Complexity, Performance and Plausibility to Meta Learn Plasticity Rules in Recurrent Spiking Networks.” <i>PLoS Computational Biology</i>. Public Library of Science, 2025. <a href=\"https://doi.org/10.1371/journal.pcbi.1012910\">https://doi.org/10.1371/journal.pcbi.1012910</a>."},"_id":"19640","article_processing_charge":"Yes","oa_version":"Published Version","day":"24","intvolume":"        21","department":[{"_id":"TiVo"}],"article_type":"original","scopus_import":"1","abstract":[{"lang":"eng","text":"Synaptic plasticity is a key player in the brain’s life-long learning abilities. However, due to experimental limitations, the mechanistic link between synaptic plasticity rules and the network-level computations they enable remain opaque. Here we use evolutionary strategies (ES) to meta learn local co-active plasticity rules in large recurrent spiking networks with excitatory (E) and inhibitory (I) neurons, using parameterizations of increasing complexity. We discover rules that robustly stabilize network dynamics for all four synapse types acting in isolation (E-to-E, E-to-I, I-to-E and I-to-I). More complex functions such as familiarity detection can also be included in the search constraints. However, our meta learning strategy begins to fail for co-active rules of increasing complexity, as it is challenging to devise loss functions that effectively constrain network dynamics to plausible solutions a priori. Moreover, in line with previous work, we can find multiple degenerate solutions with identical network behaviour. As a local optimization strategy, ES provides one solution at a time and makes exploration of this degeneracy cumbersome. Regardless, we can glean the interdependecies of various plasticity parameters by considering the covariance matrix learned alongside the optimal rule with ES. Our work provides a proof of principle for the success of machine-learning-guided discovery of plasticity rules in large spiking networks, and points at the necessity of more elaborate search strategies going forward."}],"date_updated":"2026-05-06T13:17:52Z","date_created":"2025-05-04T22:02:31Z","external_id":{"isi":["001474257000002"],"pmid":["40273284 "]},"title":"Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks","author":[{"full_name":"Confavreux, Basile J","id":"C7610134-B532-11EA-BD9F-F5753DDC885E","first_name":"Basile J","last_name":"Confavreux"},{"last_name":"Agnes","first_name":"Everton J.","full_name":"Agnes, Everton J."},{"last_name":"Zenke","first_name":"Friedemann","full_name":"Zenke, Friedemann"},{"full_name":"Sprekeler, Henning","first_name":"Henning","last_name":"Sprekeler"},{"orcid":"0000-0003-3295-6181","last_name":"Vogels","first_name":"Tim P","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"}],"project":[{"name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","grant_number":"819603","call_identifier":"H2020","_id":"0aacfa84-070f-11eb-9043-d7eb2c709234"},{"grant_number":"214316/Z/18/Z","name":"What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent neuronal networks.","_id":"c084a126-5a5b-11eb-8a69-d75314a70a87"}],"article_number":"e1012910","corr_author":"1","OA_type":"gold","date_published":"2025-04-24T00:00:00Z","publication":"PLoS Computational Biology","file_date_updated":"2025-05-05T11:17:49Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","pmid":1,"status":"public","ec_funded":1,"publication_identifier":{"eissn":["1553-7358"],"issn":["1553-734X"]},"volume":21,"OA_place":"publisher","type":"journal_article","APC_amount":"3237,62 EUR","acknowledgement":"We would like to thank Chaitanya Chintaluri, Nicoleta Condruz and Douglas Feitosa Tomé for insightful discussions. This project has received funding from the HORIZON EUROPE European Research Council (ERC) consolidator grant\r\n(SYNAPSEEK, awarded to TV), a Wellcome Trust Sir Henry Dale Research Fellowship (WT100000, awarded to TV), a Wellcome Trust Senior Research Fellowship (214316/Z/18/Z, awarded to TV), and a Sir Henry Wellcome\r\nFellowship (110124/Z/15/Z, awarded to FZ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","DOAJ_listed":"1","isi":1,"month":"04","doi":"10.1371/journal.pcbi.1012910","issue":"4","related_material":{"link":[{"url":"https://github.com/VogelsLab/SpikES","relation":"software"}]},"has_accepted_license":"1","PlanS_conform":"1","file":[{"checksum":"6437a1aab52813ab7e310e3b4fb36e3b","file_size":9771636,"content_type":"application/pdf","date_updated":"2025-05-05T11:17:49Z","file_name":"2025_PLoSCompBio_Confavreux.pdf","date_created":"2025-05-05T11:17:49Z","relation":"main_file","access_level":"open_access","success":1,"creator":"dernst","file_id":"19654"}],"language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2025","oa":1},{"volume":180,"OA_place":"publisher","publication_identifier":{"eissn":["1879-2782"],"issn":["0893-6080"]},"status":"public","ec_funded":1,"acknowledgement":"A.P. is grateful to Chaitanya Chintaluri, Douglas Feitosa Tomé, and Tim P. Vogels for useful discussions. This work was supported by a European Research Council Consolidator Grant (SYNAPSEEK, 819603, to Tim P. Vogels).","type":"journal_article","month":"12","isi":1,"year":"2024","oa":1,"file":[{"file_id":"18825","success":1,"creator":"dernst","access_level":"open_access","relation":"main_file","date_created":"2025-01-13T08:26:08Z","content_type":"application/pdf","checksum":"6a194323234e01d4ae725f674529cdb1","file_size":6162281,"file_name":"2024_NeuralNetworks_Zendrikov.pdf","date_updated":"2025-01-13T08:26:08Z"}],"language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"doi":"10.1016/j.neunet.2024.106589","has_accepted_license":"1","quality_controlled":"1","citation":{"mla":"Zendrikov, Dmitrii, and Alexander Paraskevov. “The Vitals for Steady Nucleation Maps of Spontaneous Spiking Coherence in Autonomous Two-Dimensional Neuronal Networks.” <i>Neural Networks</i>, vol. 180, 106589, Elsevier, 2024, doi:<a href=\"https://doi.org/10.1016/j.neunet.2024.106589\">10.1016/j.neunet.2024.106589</a>.","short":"D. Zendrikov, A. Paraskevov, Neural Networks 180 (2024).","ieee":"D. Zendrikov and A. Paraskevov, “The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks,” <i>Neural Networks</i>, vol. 180. Elsevier, 2024.","ista":"Zendrikov D, Paraskevov A. 2024. The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks. Neural Networks. 180, 106589.","chicago":"Zendrikov, Dmitrii, and Alexander Paraskevov. “The Vitals for Steady Nucleation Maps of Spontaneous Spiking Coherence in Autonomous Two-Dimensional Neuronal Networks.” <i>Neural Networks</i>. Elsevier, 2024. <a href=\"https://doi.org/10.1016/j.neunet.2024.106589\">https://doi.org/10.1016/j.neunet.2024.106589</a>.","apa":"Zendrikov, D., &#38; Paraskevov, A. (2024). The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks. <i>Neural Networks</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.neunet.2024.106589\">https://doi.org/10.1016/j.neunet.2024.106589</a>","ama":"Zendrikov D, Paraskevov A. The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks. <i>Neural Networks</i>. 2024;180. doi:<a href=\"https://doi.org/10.1016/j.neunet.2024.106589\">10.1016/j.neunet.2024.106589</a>"},"ddc":["570"],"publisher":"Elsevier","article_type":"original","scopus_import":"1","intvolume":"       180","department":[{"_id":"TiVo"}],"day":"01","_id":"17886","oa_version":"Published Version","article_processing_charge":"Yes (via OA deal)","project":[{"_id":"0aacfa84-070f-11eb-9043-d7eb2c709234","call_identifier":"H2020","grant_number":"819603","name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning."}],"date_created":"2024-09-08T22:01:10Z","external_id":{"isi":["001316474600001"],"pmid":["39217864"]},"title":"The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks","author":[{"full_name":"Zendrikov, Dmitrii","last_name":"Zendrikov","first_name":"Dmitrii"},{"id":"d05e3c56-9262-11ed-9231-be692464e5ac","full_name":"Paraskevov, Alexander","last_name":"Paraskevov","first_name":"Alexander"}],"date_updated":"2025-09-08T09:12:20Z","abstract":[{"text":"Thin pancake-like neuronal networks cultured on top of a planar microelectrode array have been extensively tried out in neuroengineering, as a substrate for the mobile robot’s control unit, i.e., as a cyborg’s brain. Most of these attempts failed due to intricate self-organizing dynamics in the neuronal systems. In particular, the networks may exhibit an emergent spatial map of steady nucleation sites (“n-sites”) of spontaneous population spikes. Being unpredictable and independent of the surface electrode locations, the n-sites drastically change local ability of the network to generate spikes. Here, using a spiking neuronal network model with generative spatially-embedded connectome, we systematically show in simulations that the number, location, and relative activity of spontaneously formed n-sites (“the vitals”) crucially depend on the samplings of three distributions: (1) the network distribution of neuronal excitability, (2) the distribution of connections between neurons of the network, and (3) the distribution of maximal amplitudes of a single synaptic current pulse. Moreover, blocking the dynamics of a small fraction (about 4%) of non-pacemaker neurons having the highest excitability was enough to completely suppress the occurrence of population spikes and their n-sites. This key result is explained theoretically. Remarkably, the n-sites occur taking into account only short-term synaptic plasticity, i.e., without a Hebbian-type plasticity. As the spiking network model used in this study is strictly deterministic, all simulation results can be accurately reproduced. The model, which has already demonstrated a very high richness-to-complexity ratio, can also be directly extended into the three-dimensional case, e.g., for targeting peculiarities of spiking dynamics in cerebral (or brain) organoids. We recommend the model as an excellent illustrative tool for teaching network-level computational neuroscience, complementing a few benchmark models.","lang":"eng"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","pmid":1,"publication_status":"published","publication":"Neural Networks","file_date_updated":"2025-01-13T08:26:08Z","OA_type":"hybrid","date_published":"2024-12-01T00:00:00Z","article_number":"106589","corr_author":"1"},{"citation":{"chicago":"Vijatovic, David, Florina Alexandra  Toma, Zoe P Harrington, Christoph M Sommer, Robert Hauschild, Alexandra J. Trevisan, Phillip Chapman, et al. “Spinal Neuron Diversity Scales Exponentially with Swim-to-Limb Transformation during Frog Metamorphosis.” <i>BioRxiv</i>, n.d. <a href=\"https://doi.org/10.1101/2024.09.20.614050\">https://doi.org/10.1101/2024.09.20.614050</a>.","ama":"Vijatovic D, Toma FA, Harrington ZP, et al. Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis. <i>bioRxiv</i>. doi:<a href=\"https://doi.org/10.1101/2024.09.20.614050\">10.1101/2024.09.20.614050</a>","apa":"Vijatovic, D., Toma, F. A., Harrington, Z. P., Sommer, C. M., Hauschild, R., Trevisan, A. J., … Sweeney, L. B. (n.d.). Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis. <i>bioRxiv</i>. <a href=\"https://doi.org/10.1101/2024.09.20.614050\">https://doi.org/10.1101/2024.09.20.614050</a>","short":"D. Vijatovic, F.A. Toma, Z.P. Harrington, C.M. Sommer, R. Hauschild, A.J. Trevisan, P. Chapman, M. Julseth, S. Brenner-Morton, M.I. Gabitto, J.S. Dasen, J.B. Bikoff, L.B. Sweeney, BioRxiv (n.d.).","mla":"Vijatovic, David, et al. “Spinal Neuron Diversity Scales Exponentially with Swim-to-Limb Transformation during Frog Metamorphosis.” <i>BioRxiv</i>, doi:<a href=\"https://doi.org/10.1101/2024.09.20.614050\">10.1101/2024.09.20.614050</a>.","ieee":"D. Vijatovic <i>et al.</i>, “Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis,” <i>bioRxiv</i>. .","ista":"Vijatovic D, Toma FA, Harrington ZP, Sommer CM, Hauschild R, Trevisan AJ, Chapman P, Julseth M, Brenner-Morton S, Gabitto MI, Dasen JS, Bikoff JB, Sweeney LB. Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis. bioRxiv, <a href=\"https://doi.org/10.1101/2024.09.20.614050\">10.1101/2024.09.20.614050</a>."},"OA_place":"repository","status":"public","acknowledged_ssus":[{"_id":"Bio"}],"department":[{"_id":"LoSw"},{"_id":"TiVo"},{"_id":"Bio"},{"_id":"NiBa"}],"acknowledgement":"We would like to thank the members of the Sweeney Lab (especially Stavros Papadopoulos and\r\nSophie Gobeil) for their contributions to this project and, in addition to the lab, Graziana Gatto\r\nand Mario de Bono, for discussion, and support. We are also grateful to Tom Jessell and Chris\r\nKintner for their scientific insight and mentorship during the conception of this project. This\r\nproject would also not have been possible with the technical support of the Matthias Nowak,\r\nVerena Mayer and the Aquatics as well as the Imaging and Optics Facility support teams\r\n(ISTA). In addition, we thank our funding sources for providing the resources to do these\r\nexperiments: FTI Strategy Lower Austria Dissertation Grant Number FT121-D-046 (D.V.);\r\nHorizon Europe ERC Starting Grant Number 101041551 (L.B.S., F.A.T. and D.V); Special\r\nResearch Program (SFB) of the Austrian Science Fund (FWF) Project number F7814-B (L.B.S);\r\nNINDS 5R35NS116858 (J.S.D); CZI grant DAF2020-225401 (DOI): 10.37921/120055ratwvi\r\n(R.H.); NIH grant number R01NS123116 (J.B.B); American Lebanese Syrian Associated\r\nCharities (ALSAC) (J.B.B.); German Academic Exchange Service (DAAD) IFI Grant Number\r\n57515251-91853472 (Z.H.); and Project A.L.S. (S.B-M.). ","article_processing_charge":"No","oa_version":"Preprint","type":"preprint","_id":"19520","day":"27","author":[{"first_name":"David","last_name":"Vijatovic","id":"cf391e77-ec3c-11ea-a124-d69323410b58","full_name":"Vijatovic, David"},{"first_name":"Florina Alexandra ","last_name":"Toma","full_name":"Toma, Florina Alexandra ","id":"2f73f876-f128-11eb-9611-b96b5a30cb0e"},{"id":"a8144562-32c9-11ee-b5ce-d9800628bda2","full_name":"Harrington, Zoe P","orcid":"0009-0008-0158-4032","first_name":"Zoe P","last_name":"Harrington"},{"orcid":"0000-0003-1216-9105","first_name":"Christoph M","last_name":"Sommer","full_name":"Sommer, Christoph M","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0001-9843-3522","first_name":"Robert","last_name":"Hauschild","full_name":"Hauschild, Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Alexandra J.","last_name":"Trevisan","full_name":"Trevisan, Alexandra J."},{"last_name":"Chapman","first_name":"Phillip","full_name":"Chapman, Phillip"},{"last_name":"Julseth","first_name":"Mara","full_name":"Julseth, Mara","id":"1cf464b2-dc7d-11ea-9b2f-f9b1aa9417d1"},{"full_name":"Brenner-Morton, Susan","first_name":"Susan","last_name":"Brenner-Morton"},{"full_name":"Gabitto, Mariano I.","first_name":"Mariano I.","last_name":"Gabitto"},{"first_name":"Jeremy S.","last_name":"Dasen","full_name":"Dasen, Jeremy S."},{"full_name":"Bikoff, Jay B.","last_name":"Bikoff","first_name":"Jay B."},{"id":"56BE8254-C4F0-11E9-8E45-0B23E6697425","full_name":"Sweeney, Lora Beatrice Jaeger","orcid":"0000-0001-9242-5601","first_name":"Lora Beatrice Jaeger","last_name":"Sweeney"}],"title":"Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis","date_created":"2025-04-07T08:48:28Z","project":[{"_id":"bd73af52-d553-11ed-ba76-912049f0ac7a","grant_number":"FTI21-D-046","name":"Development of V1 interneuron diversity during swim-to-walk transition of Xenopus metamorphosis"},{"_id":"ebb66355-77a9-11ec-83b8-b8ac210a4dae","grant_number":"101041551","name":"Development and Evolution of Tetrapod Motor Circuits"},{"grant_number":"CZI01","name":"Tools for automation and feedback microscopy","_id":"c08e9ad1-5a5b-11eb-8a69-9d1cf3b07473"}],"month":"09","abstract":[{"text":"Vertebrates exhibit a wide range of motor behaviors, ranging from swimming to complex limb-based movements. Here we take advantage of frog metamorphosis, which captures a swim-to-limb-based movement transformation during the development of a single organism, to explore changes in the underlying spinal circuits. We find that the tadpole spinal cord contains small and largely homogeneous populations of motor neurons (MNs) and V1 interneurons (V1s) at early escape swimming stages. These neuronal populations only modestly increase in number and subtype heterogeneity with the emergence of free swimming. In contrast, during frog metamorphosis and the emergence of limb movement, there is a dramatic expansion of MN and V1 interneuron number and transcriptional heterogeneity, culminating in cohorts of neurons that exhibit striking molecular similarity to mammalian motor circuits. CRISPR/Cas9-mediated gene disruption of the limb MN and V1 determinants FoxP1 and Engrailed-1, respectively, results in severe but selective deficits in tail and limb function. Our work thus demonstrates that neural diversity scales exponentially with increasing behavioral complexity and illustrates striking evolutionary conservation in the molecular organization and function of motor circuits across species.","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/2024.09.20.614050"}],"date_updated":"2025-05-14T11:40:13Z","publication":"bioRxiv","language":[{"iso":"eng"}],"oa":1,"publication_status":"submitted","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","corr_author":"1","doi":"10.1101/2024.09.20.614050","date_published":"2024-09-27T00:00:00Z","OA_type":"green"},{"isi":1,"month":"01","has_accepted_license":"1","related_material":{"link":[{"url":"https://github.com/ChrisCurrin/pv-kcnc2 ","relation":"software"}]},"doi":"10.1073/pnas.2307776121","issue":"3","oa":1,"year":"2024","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"file":[{"file_id":"19613","creator":"dernst","success":1,"access_level":"open_access","relation":"main_file","date_created":"2025-04-23T13:51:16Z","file_name":"2024_PNAS_Clatot.pdf","date_updated":"2025-04-23T13:51:16Z","checksum":"f498c643be81895dd3a69ee90115a782","file_size":3060109,"content_type":"application/pdf"}],"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["1091-6490"]},"ec_funded":1,"status":"public","OA_place":"publisher","volume":121,"type":"journal_article","acknowledgement":"This work was supported by an ERC Consolidator Grant (SYNAPSEEK) to T.P.V., the NOMIS Foundation through the NOMIS Fellowships program at IST Austria to C.B.C., a Jefferson Synaptic Biology Center Pilot Project Grant to M.C., NIH NINDS U54 NS108874 (PI, Alfred L. George), and NIH NINDS R01 NS122887 to E.M.G. The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at the PDC Center for High-Performance Computing, KTH Royal Institute of Technology, partially funded by the Swedish Research Council through grant agreement no. 2018-05973. We thank Akshay Sridhar for the fruitful discussion of the project.","date_updated":"2025-09-04T11:47:47Z","abstract":[{"text":"De novo heterozygous variants in KCNC2 encoding the voltage-gated potassium (K+) channel subunit Kv3.2 are a recently described cause of developmental and epileptic encephalopathy (DEE). A de novo variant in KCNC2 c.374G > A (p.Cys125Tyr) was identified via exome sequencing in a patient with DEE. Relative to wild-type Kv3.2, Kv3.2-p.Cys125Tyr induces K+ currents exhibiting a large hyperpolarizing shift in the voltage dependence of activation, accelerated activation, and delayed deactivation consistent with a relative stabilization of the open conformation, along with increased current density. Leveraging the cryogenic electron microscopy (cryo-EM) structure of Kv3.1, molecular dynamic simulations suggest that a strong π-π stacking interaction between the variant Tyr125 and Tyr156 in the α-6 helix of the T1 domain promotes a relative stabilization of the open conformation of the channel, which underlies the observed gain of function. A multicompartment computational model of a Kv3-expressing parvalbumin-positive cerebral cortex fast-spiking γ-aminobutyric acidergic (GABAergic) interneuron (PV-IN) demonstrates how the Kv3.2-Cys125Tyr variant impairs neuronal excitability and dysregulates inhibition in cerebral cortex circuits to explain the resulting epilepsy.","lang":"eng"}],"project":[{"_id":"0aacfa84-070f-11eb-9043-d7eb2c709234","grant_number":"819603","name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","call_identifier":"H2020"}],"title":"A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction","author":[{"last_name":"Clatot","first_name":"Jerome","full_name":"Clatot, Jerome"},{"last_name":"Currin","first_name":"Christopher","orcid":"0000-0002-4809-5059","id":"e8321fc5-3091-11eb-8a53-83f309a11ac9","full_name":"Currin, Christopher"},{"last_name":"Liang","first_name":"Qiansheng","full_name":"Liang, Qiansheng"},{"full_name":"Pipatpolkai, Tanadet","last_name":"Pipatpolkai","first_name":"Tanadet"},{"first_name":"Shavonne L.","last_name":"Massey","full_name":"Massey, Shavonne L."},{"last_name":"Helbig","first_name":"Ingo","full_name":"Helbig, Ingo"},{"full_name":"Delemotte, Lucie","last_name":"Delemotte","first_name":"Lucie"},{"orcid":"0000-0003-3295-6181","last_name":"Vogels","first_name":"Tim P","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"},{"full_name":"Covarrubias, Manuel","last_name":"Covarrubias","first_name":"Manuel"},{"last_name":"Goldberg","first_name":"Ethan M.","full_name":"Goldberg, Ethan M."}],"date_created":"2024-01-21T23:00:56Z","external_id":{"pmid":["38194456"],"isi":["001167401000001"]},"date_published":"2024-01-16T00:00:00Z","OA_type":"hybrid","article_number":"e2307776121","publication_status":"published","pmid":1,"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","file_date_updated":"2025-04-23T13:51:16Z","publication":"Proceedings of the National Academy of Sciences of the United States of America","publisher":"National Academy of Sciences","quality_controlled":"1","citation":{"apa":"Clatot, J., Currin, C., Liang, Q., Pipatpolkai, T., Massey, S. L., Helbig, I., … Goldberg, E. M. (2024). A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction. <i>Proceedings of the National Academy of Sciences of the United States of America</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.2307776121\">https://doi.org/10.1073/pnas.2307776121</a>","ama":"Clatot J, Currin C, Liang Q, et al. A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction. <i>Proceedings of the National Academy of Sciences of the United States of America</i>. 2024;121(3). doi:<a href=\"https://doi.org/10.1073/pnas.2307776121\">10.1073/pnas.2307776121</a>","chicago":"Clatot, Jerome, Christopher Currin, Qiansheng Liang, Tanadet Pipatpolkai, Shavonne L. Massey, Ingo Helbig, Lucie Delemotte, Tim P Vogels, Manuel Covarrubias, and Ethan M. Goldberg. “A Structurally Precise Mechanism Links an Epilepsy-Associated KCNC2 Potassium Channel Mutation to Interneuron Dysfunction.” <i>Proceedings of the National Academy of Sciences of the United States of America</i>. National Academy of Sciences, 2024. <a href=\"https://doi.org/10.1073/pnas.2307776121\">https://doi.org/10.1073/pnas.2307776121</a>.","ista":"Clatot J, Currin C, Liang Q, Pipatpolkai T, Massey SL, Helbig I, Delemotte L, Vogels TP, Covarrubias M, Goldberg EM. 2024. A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction. Proceedings of the National Academy of Sciences of the United States of America. 121(3), e2307776121.","ieee":"J. Clatot <i>et al.</i>, “A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction,” <i>Proceedings of the National Academy of Sciences of the United States of America</i>, vol. 121, no. 3. National Academy of Sciences, 2024.","short":"J. Clatot, C. Currin, Q. Liang, T. Pipatpolkai, S.L. Massey, I. Helbig, L. Delemotte, T.P. Vogels, M. Covarrubias, E.M. Goldberg, Proceedings of the National Academy of Sciences of the United States of America 121 (2024).","mla":"Clatot, Jerome, et al. “A Structurally Precise Mechanism Links an Epilepsy-Associated KCNC2 Potassium Channel Mutation to Interneuron Dysfunction.” <i>Proceedings of the National Academy of Sciences of the United States of America</i>, vol. 121, no. 3, e2307776121, National Academy of Sciences, 2024, doi:<a href=\"https://doi.org/10.1073/pnas.2307776121\">10.1073/pnas.2307776121</a>."},"ddc":["570"],"day":"16","article_processing_charge":"Yes (in subscription journal)","oa_version":"Published Version","_id":"14841","article_type":"original","scopus_import":"1","department":[{"_id":"TiVo"}],"intvolume":"       121"},{"acknowledgement":"We thank S. Erisken from Inscopix for helping us establish in vivo one-photon calcium imaging for this work. We thank K. Su at Tsinghua University for assistance with this work. This work was funded by the President’s PhD Scholarship from Imperial College London (D.F.T.), the Wellcome Trust (225412/Z/22/Z) (S.S.), the Biotechnology and Biological Sciences Research Council (BB/N013956/1 and BB/N019008/1) (C.C.), the Wellcome Trust (200790/Z/16/Z) (C.C.), the Simons Foundation (564408) (C.C.) and the Engineering and Physical Sciences Research Council (EP/R035806/1) (CC). The School of Life Sciences and the IDG/McGovern Institute for Brain Research supported Y.Z. The Warren Alpert Distinguished Scholar Award and National Institutes of Health 1K99NS125131-01 supported D.S.R.","type":"journal_article","volume":27,"status":"public","publication_identifier":{"eissn":["1546-1726"],"issn":["1097-6256"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"file_name":"2024_NatureNeuroscience_FeitosaTome.pdf","date_updated":"2024-07-16T12:15:19Z","content_type":"application/pdf","checksum":"c509fcad757e4c1c153e857e55c20083","file_size":15830346,"date_created":"2024-07-16T12:15:19Z","relation":"main_file","access_level":"open_access","creator":"dernst","success":1,"file_id":"17268"}],"language":[{"iso":"eng"}],"oa":1,"year":"2024","has_accepted_license":"1","page":"561-572","related_material":{"record":[{"relation":"research_data","status":"public","id":"14892"}]},"doi":"10.1038/s41593-023-01551-w","month":"03","isi":1,"department":[{"_id":"TiVo"}],"intvolume":"        27","article_type":"original","scopus_import":"1","oa_version":"Published Version","article_processing_charge":"Yes (in subscription journal)","_id":"14887","day":"01","ddc":["570"],"citation":{"ista":"Feitosa Tomé D, Zhang Y, Aida T, Mosto O, Lu Y, Chen M, Sadeh S, Roy DS, Clopath C. 2024. Dynamic and selective engrams emerge with memory consolidation. Nature Neuroscience. 27, 561–572.","short":"D. Feitosa Tomé, Y. Zhang, T. Aida, O. Mosto, Y. Lu, M. Chen, S. Sadeh, D.S. Roy, C. Clopath, Nature Neuroscience 27 (2024) 561–572.","mla":"Feitosa Tomé, Douglas, et al. “Dynamic and Selective Engrams Emerge with Memory Consolidation.” <i>Nature Neuroscience</i>, vol. 27, Springer Nature, 2024, pp. 561–72, doi:<a href=\"https://doi.org/10.1038/s41593-023-01551-w\">10.1038/s41593-023-01551-w</a>.","ieee":"D. Feitosa Tomé <i>et al.</i>, “Dynamic and selective engrams emerge with memory consolidation,” <i>Nature Neuroscience</i>, vol. 27. Springer Nature, pp. 561–572, 2024.","apa":"Feitosa Tomé, D., Zhang, Y., Aida, T., Mosto, O., Lu, Y., Chen, M., … Clopath, C. (2024). Dynamic and selective engrams emerge with memory consolidation. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-023-01551-w\">https://doi.org/10.1038/s41593-023-01551-w</a>","ama":"Feitosa Tomé D, Zhang Y, Aida T, et al. Dynamic and selective engrams emerge with memory consolidation. <i>Nature Neuroscience</i>. 2024;27:561-572. doi:<a href=\"https://doi.org/10.1038/s41593-023-01551-w\">10.1038/s41593-023-01551-w</a>","chicago":"Feitosa Tomé, Douglas, Ying Zhang, Tomomi Aida, Olivia Mosto, Yifeng Lu, Mandy Chen, Sadra Sadeh, Dheeraj S. Roy, and Claudia Clopath. “Dynamic and Selective Engrams Emerge with Memory Consolidation.” <i>Nature Neuroscience</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41593-023-01551-w\">https://doi.org/10.1038/s41593-023-01551-w</a>."},"quality_controlled":"1","publisher":"Springer Nature","file_date_updated":"2024-07-16T12:15:19Z","publication":"Nature Neuroscience","pmid":1,"publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","corr_author":"1","date_published":"2024-03-01T00:00:00Z","title":"Dynamic and selective engrams emerge with memory consolidation","author":[{"last_name":"Feitosa Tomé","first_name":"Douglas","id":"0eed2d40-3d48-11ec-8d38-f789cc2e40b2","full_name":"Feitosa Tomé, Douglas"},{"last_name":"Zhang","first_name":"Ying","full_name":"Zhang, Ying"},{"last_name":"Aida","first_name":"Tomomi","full_name":"Aida, Tomomi"},{"last_name":"Mosto","first_name":"Olivia","full_name":"Mosto, Olivia"},{"full_name":"Lu, Yifeng","first_name":"Yifeng","last_name":"Lu"},{"first_name":"Mandy","last_name":"Chen","full_name":"Chen, Mandy"},{"last_name":"Sadeh","first_name":"Sadra","full_name":"Sadeh, Sadra"},{"full_name":"Roy, Dheeraj S.","last_name":"Roy","first_name":"Dheeraj S."},{"first_name":"Claudia","last_name":"Clopath","full_name":"Clopath, Claudia"}],"external_id":{"pmid":["38243089"],"isi":["001145442300001"]},"date_created":"2024-01-28T23:01:43Z","abstract":[{"lang":"eng","text":"Episodic memories are encoded by experience-activated neuronal ensembles that remain necessary and sufficient for recall. However, the temporal evolution of memory engrams after initial encoding is unclear. In this study, we employed computational and experimental approaches to examine how the neural composition and selectivity of engrams change with memory consolidation. Our spiking neural network model yielded testable predictions: memories transition from unselective to selective as neurons drop out of and drop into engrams; inhibitory activity during recall is essential for memory selectivity; and inhibitory synaptic plasticity during memory consolidation is critical for engrams to become selective. Using activity-dependent labeling, longitudinal calcium imaging and a combination of optogenetic and chemogenetic manipulations in mouse dentate gyrus, we conducted contextual fear conditioning experiments that supported our model’s predictions. Our results reveal that memory engrams are dynamic and that changes in engram composition mediated by inhibitory plasticity are crucial for the emergence of memory selectivity."}],"date_updated":"2025-04-23T07:40:21Z"},{"date_updated":"2025-09-04T13:08:54Z","abstract":[{"lang":"eng","text":"Interpretation of extracellular recordings can be challenging due to the long range of electric field. This challenge can be mitigated by estimating the current source density (CSD). Here we introduce kCSD-python, an open Python package implementing Kernel Current Source Density (kCSD) method and related tools to facilitate CSD analysis of experimental data and the interpretation of results. We show how to counter the limitations imposed by noise and assumptions in the method itself. kCSD-python allows CSD estimation for an arbitrary distribution of electrodes in 1D, 2D, and 3D, assuming distributions of sources in tissue, a slice, or in a single cell, and includes a range of diagnostic aids. We demonstrate its features in a Jupyter Notebook tutorial which illustrates a typical analytical workflow and main functionalities useful in validating analysis results."}],"external_id":{"isi":["001190689800001"],"pmid":["38484020"]},"date_created":"2024-03-24T23:00:59Z","title":"kCSD-python, reliable current source density estimation with quality control","author":[{"first_name":"Chaitanya","last_name":"Chintaluri","id":"E4EDB536-3485-11EA-98D2-20AF3DDC885E","full_name":"Chintaluri, Chaitanya"},{"first_name":"Marta","last_name":"Bejtka","full_name":"Bejtka, Marta"},{"full_name":"Sredniawa, Wladyslaw","last_name":"Sredniawa","first_name":"Wladyslaw"},{"full_name":"Czerwinski, Michal","first_name":"Michal","last_name":"Czerwinski"},{"last_name":"Dzik","first_name":"Jakub M.","full_name":"Dzik, Jakub M."},{"full_name":"Jedrzejewska-Szmek, Joanna","first_name":"Joanna","last_name":"Jedrzejewska-Szmek"},{"full_name":"Wojciki, Daniel K.","first_name":"Daniel K.","last_name":"Wojciki"}],"OA_type":"gold","date_published":"2024-03-14T00:00:00Z","article_number":"e1011941","corr_author":"1","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","pmid":1,"publication_status":"published","publication":"PLoS Computational Biology","file_date_updated":"2025-06-25T05:47:36Z","publisher":"Public Library of Science","quality_controlled":"1","citation":{"ama":"Chintaluri C, Bejtka M, Sredniawa W, et al. kCSD-python, reliable current source density estimation with quality control. <i>PLoS Computational Biology</i>. 2024;20(3). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">10.1371/journal.pcbi.1011941</a>","apa":"Chintaluri, C., Bejtka, M., Sredniawa, W., Czerwinski, M., Dzik, J. M., Jedrzejewska-Szmek, J., &#38; Wojciki, D. K. (2024). kCSD-python, reliable current source density estimation with quality control. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">https://doi.org/10.1371/journal.pcbi.1011941</a>","chicago":"Chintaluri, Chaitanya, Marta Bejtka, Wladyslaw Sredniawa, Michal Czerwinski, Jakub M. Dzik, Joanna Jedrzejewska-Szmek, and Daniel K. Wojciki. “KCSD-Python, Reliable Current Source Density Estimation with Quality Control.” <i>PLoS Computational Biology</i>. Public Library of Science, 2024. <a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">https://doi.org/10.1371/journal.pcbi.1011941</a>.","ista":"Chintaluri C, Bejtka M, Sredniawa W, Czerwinski M, Dzik JM, Jedrzejewska-Szmek J, Wojciki DK. 2024. kCSD-python, reliable current source density estimation with quality control. PLoS Computational Biology. 20(3), e1011941.","ieee":"C. Chintaluri <i>et al.</i>, “kCSD-python, reliable current source density estimation with quality control,” <i>PLoS Computational Biology</i>, vol. 20, no. 3. Public Library of Science, 2024.","short":"C. Chintaluri, M. Bejtka, W. Sredniawa, M. Czerwinski, J.M. Dzik, J. Jedrzejewska-Szmek, D.K. Wojciki, PLoS Computational Biology 20 (2024).","mla":"Chintaluri, Chaitanya, et al. “KCSD-Python, Reliable Current Source Density Estimation with Quality Control.” <i>PLoS Computational Biology</i>, vol. 20, no. 3, e1011941, Public Library of Science, 2024, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">10.1371/journal.pcbi.1011941</a>."},"ddc":["000","570"],"day":"14","_id":"15169","article_processing_charge":"Yes","oa_version":"Published Version","article_type":"original","scopus_import":"1","intvolume":"        20","department":[{"_id":"TiVo"}],"isi":1,"DOAJ_listed":"1","month":"03","doi":"10.1371/journal.pcbi.1011941","issue":"3","has_accepted_license":"1","related_material":{"link":[{"url":"https://github.com/Neuroinflab/kCSD-python","relation":"software"}]},"year":"2024","oa":1,"language":[{"iso":"eng"}],"file":[{"creator":"dernst","success":1,"access_level":"open_access","file_id":"19897","date_updated":"2025-06-25T05:47:36Z","file_name":"2024_PLoSCompBio_Chintaluri.pdf","file_size":2540277,"checksum":"c09718d0d09614642d877d0716ce32e8","content_type":"application/pdf","relation":"main_file","date_created":"2025-06-25T05:47:36Z"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"publication_identifier":{"eissn":["1553-7358"],"issn":["1553-734X"]},"status":"public","volume":20,"OA_place":"publisher","type":"journal_article","acknowledgement":"The Python implementation of kCSD was started by Grzegorz Parka during Google Summer of Code project through the International Neuroinformatics Coordinating Facility. Jan Mąka implemented the first Python version of skCSD class. This work was supported by the Polish National Science Centre (2013/08/W/NZ4/00691 to DKW; 2015/17/B/ST7/04123 to DKW). "},{"has_accepted_license":"1","page":"964-974","doi":"10.1038/s41593-024-01597-4","oa":1,"year":"2024","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"relation":"main_file","date_created":"2025-06-25T08:45:32Z","file_name":"2025_NatureNeuroscience_Agnes.pdf","date_updated":"2025-06-25T08:45:32Z","content_type":"application/pdf","file_size":10508018,"checksum":"dfca68a24749575b912b3a78a7de4516","file_id":"19902","creator":"dernst","success":1,"access_level":"open_access"}],"language":[{"iso":"eng"}],"isi":1,"month":"05","type":"journal_article","acknowledgement":"We thank C. Currin, B. Podlaski and the members of the Vogels group for fruitful discussions. E.J.A. and T.P.V. were supported by a Research Project Grant from the Leverhulme Trust (RPG-2016-446; TPV), a Sir Henry Dale Fellowship from the Wellcome Trust and the Royal Society (WT100000; T.P.V.), a Wellcome Trust Senior Research Fellowship (214316/Z/18/Z; T.P.V.) and a European Research Council Consolidator Grant (SYNAPSEEK, 819603; T.P.V.). For the purpose of open access, the authors have applied a CC BY public copyright license to any author accepted manuscript version arising from this submission. Open access funding provided by University of Basel.","publication_identifier":{"eissn":["1546-1726"],"issn":["1097-6256"]},"ec_funded":1,"status":"public","OA_place":"publisher","volume":27,"date_published":"2024-05-01T00:00:00Z","OA_type":"hybrid","pmid":1,"publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication":"Nature Neuroscience","file_date_updated":"2025-06-25T08:45:32Z","date_updated":"2025-09-04T13:06:06Z","abstract":[{"text":"The brain’s functionality is developed and maintained through synaptic plasticity. As synapses undergo plasticity, they also affect each other. The nature of such ‘co-dependency’ is difficult to disentangle experimentally, because multiple synapses must be monitored simultaneously. To help understand the experimentally observed phenomena, we introduce a framework that formalizes synaptic co-dependency between different connection types. The resulting model explains how inhibition can gate excitatory plasticity while neighboring excitatory–excitatory interactions determine the strength of long-term potentiation. Furthermore, we show how the interplay between excitatory and inhibitory synapses can account for the quick rise and long-term stability of a variety of synaptic weight profiles, such as orientation tuning and dendritic clustering of co-active synapses. In recurrent neuronal networks, co-dependent plasticity produces rich and stable motor cortex-like dynamics with high input sensitivity. Our results suggest an essential role for the neighborly synaptic interaction during learning, connecting micro-level physiology with network-wide phenomena.","lang":"eng"}],"project":[{"_id":"0aacfa84-070f-11eb-9043-d7eb2c709234","name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","grant_number":"819603","call_identifier":"H2020"}],"title":"Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks","author":[{"full_name":"Agnes, Everton J.","last_name":"Agnes","first_name":"Everton J."},{"orcid":"0000-0003-3295-6181","last_name":"Vogels","first_name":"Tim P","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"}],"external_id":{"isi":["001190081400001"],"pmid":["38509348 "]},"date_created":"2024-03-24T23:01:00Z","day":"01","article_processing_charge":"Yes (via OA deal)","oa_version":"Published Version","_id":"15171","article_type":"original","scopus_import":"1","department":[{"_id":"TiVo"}],"intvolume":"        27","publisher":"Springer Nature","citation":{"ista":"Agnes EJ, Vogels TP. 2024. Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks. Nature Neuroscience. 27, 964–974.","mla":"Agnes, Everton J., and Tim P. Vogels. “Co-Dependent Excitatory and Inhibitory Plasticity Accounts for Quick, Stable and Long-Lasting Memories in Biological Networks.” <i>Nature Neuroscience</i>, vol. 27, Springer Nature, 2024, pp. 964–74, doi:<a href=\"https://doi.org/10.1038/s41593-024-01597-4\">10.1038/s41593-024-01597-4</a>.","short":"E.J. Agnes, T.P. Vogels, Nature Neuroscience 27 (2024) 964–974.","ieee":"E. J. Agnes and T. P. Vogels, “Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks,” <i>Nature Neuroscience</i>, vol. 27. Springer Nature, pp. 964–974, 2024.","apa":"Agnes, E. J., &#38; Vogels, T. P. (2024). Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-024-01597-4\">https://doi.org/10.1038/s41593-024-01597-4</a>","ama":"Agnes EJ, Vogels TP. Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks. <i>Nature Neuroscience</i>. 2024;27:964-974. doi:<a href=\"https://doi.org/10.1038/s41593-024-01597-4\">10.1038/s41593-024-01597-4</a>","chicago":"Agnes, Everton J., and Tim P Vogels. “Co-Dependent Excitatory and Inhibitory Plasticity Accounts for Quick, Stable and Long-Lasting Memories in Biological Networks.” <i>Nature Neuroscience</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41593-024-01597-4\">https://doi.org/10.1038/s41593-024-01597-4</a>."},"quality_controlled":"1","ddc":["570"]},{"external_id":{"isi":["001181690200005"],"pmid":["38427633"]},"date_created":"2024-04-02T11:37:32Z","author":[{"last_name":"Hall","first_name":"Siobhan Mackenzie","full_name":"Hall, Siobhan Mackenzie"},{"first_name":"Daniel","last_name":"Kochin","full_name":"Kochin, Daniel"},{"first_name":"Carmel","last_name":"Carne","full_name":"Carne, Carmel"},{"last_name":"Herterich","first_name":"Patricia","full_name":"Herterich, Patricia"},{"last_name":"Lewers","first_name":"Kristen Lenay","full_name":"Lewers, Kristen Lenay"},{"first_name":"Mohamed","last_name":"Abdelhack","full_name":"Abdelhack, Mohamed"},{"full_name":"Ramasubramanian, Arun","last_name":"Ramasubramanian","first_name":"Arun"},{"first_name":"Juno Felecia","last_name":"Michael Alphonse","full_name":"Michael Alphonse, Juno Felecia"},{"full_name":"Ung, Visotheary","first_name":"Visotheary","last_name":"Ung"},{"first_name":"Sara","last_name":"El-Gebali","full_name":"El-Gebali, Sara"},{"orcid":"0000-0002-4809-5059","last_name":"Currin","first_name":"Christopher","full_name":"Currin, Christopher","id":"e8321fc5-3091-11eb-8a53-83f309a11ac9"},{"full_name":"Plomp, Esther","first_name":"Esther","last_name":"Plomp"},{"first_name":"Rachel","last_name":"Thompson","full_name":"Thompson, Rachel"},{"full_name":"Sharan, Malvika","last_name":"Sharan","first_name":"Malvika"}],"title":"Ten simple rules for pushing boundaries of inclusion at academic events","abstract":[{"text":"Inclusion at academic events is facing increased scrutiny as the communities these events serve raise their expectations for who can practically attend. Active efforts in recent years to bring more diversity to academic events have brought progress and created momentum. However, we must reflect on these efforts and determine which underrepresented groups are being disadvantaged. Inclusion at academic events is important to ensure diversity of discourse and opinion, to help build networks, and to avoid academic siloing. All of these contribute to the development of a robust and resilient academic field. We have developed these Ten Simple Rules both to amplify the voices that have been speaking out and to celebrate the progress of many Equity, Diversity, and Inclusivity practices that continue to drive the organisation of academic events. The Rules aim to raise awareness as well as provide actionable suggestions and tools to support these initiatives further. This aims to support academic organisations such as the Deep Learning Indaba, Neuromatch Academy, the IBRO-Simons Computational Neuroscience Imbizo, Biodiversity Information Standards (TDWG), Arabs in Neuroscience, FAIRPoints, and OLS (formerly Open Life Science). This article is a call to action for organisers to reevaluate the impact and reach of their inclusive practices.","lang":"eng"}],"date_updated":"2025-09-04T13:24:19Z","file_date_updated":"2024-04-03T13:29:36Z","publication":"PLOS Computational Biology","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","pmid":1,"article_number":"e1011797","OA_type":"gold","date_published":"2024-03-01T00:00:00Z","ddc":["000"],"citation":{"ama":"Hall SM, Kochin D, Carne C, et al. Ten simple rules for pushing boundaries of inclusion at academic events. <i>PLOS Computational Biology</i>. 2024;20(3). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011797\">10.1371/journal.pcbi.1011797</a>","apa":"Hall, S. M., Kochin, D., Carne, C., Herterich, P., Lewers, K. L., Abdelhack, M., … Sharan, M. (2024). Ten simple rules for pushing boundaries of inclusion at academic events. <i>PLOS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1011797\">https://doi.org/10.1371/journal.pcbi.1011797</a>","chicago":"Hall, Siobhan Mackenzie, Daniel Kochin, Carmel Carne, Patricia Herterich, Kristen Lenay Lewers, Mohamed Abdelhack, Arun Ramasubramanian, et al. “Ten Simple Rules for Pushing Boundaries of Inclusion at Academic Events.” <i>PLOS Computational Biology</i>. Public Library of Science, 2024. <a href=\"https://doi.org/10.1371/journal.pcbi.1011797\">https://doi.org/10.1371/journal.pcbi.1011797</a>.","ista":"Hall SM, Kochin D, Carne C, Herterich P, Lewers KL, Abdelhack M, Ramasubramanian A, Michael Alphonse JF, Ung V, El-Gebali S, Currin C, Plomp E, Thompson R, Sharan M. 2024. Ten simple rules for pushing boundaries of inclusion at academic events. PLOS Computational Biology. 20(3), e1011797.","mla":"Hall, Siobhan Mackenzie, et al. “Ten Simple Rules for Pushing Boundaries of Inclusion at Academic Events.” <i>PLOS Computational Biology</i>, vol. 20, no. 3, e1011797, Public Library of Science, 2024, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011797\">10.1371/journal.pcbi.1011797</a>.","short":"S.M. Hall, D. Kochin, C. Carne, P. Herterich, K.L. Lewers, M. Abdelhack, A. Ramasubramanian, J.F. Michael Alphonse, V. Ung, S. El-Gebali, C. Currin, E. Plomp, R. Thompson, M. Sharan, PLOS Computational Biology 20 (2024).","ieee":"S. M. Hall <i>et al.</i>, “Ten simple rules for pushing boundaries of inclusion at academic events,” <i>PLOS Computational Biology</i>, vol. 20, no. 3. Public Library of Science, 2024."},"quality_controlled":"1","publisher":"Public Library of Science","intvolume":"        20","department":[{"_id":"TiVo"}],"scopus_import":"1","article_type":"original","_id":"15258","article_processing_charge":"Yes","oa_version":"Published Version","day":"01","month":"03","DOAJ_listed":"1","isi":1,"file":[{"relation":"main_file","date_created":"2024-04-03T13:29:36Z","content_type":"application/pdf","file_size":858521,"checksum":"1f0f837c5b4341f54f6347370ed8c1b7","date_updated":"2024-04-03T13:29:36Z","file_name":"2024_PloS_Hall.pdf","file_id":"15289","success":1,"creator":"dernst","access_level":"open_access"}],"language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2024","oa":1,"issue":"3","doi":"10.1371/journal.pcbi.1011797","has_accepted_license":"1","volume":20,"OA_place":"publisher","status":"public","publication_identifier":{"issn":["1553-7358"]},"acknowledgement":"We would like to recognise the feedback and ideas shared with us by all attendees during the\r\nfocus groups that contributed to the development of this paper. Acknowledgements are given\r\nto Elisee Jafsia, Umar Farouk Ahmad, Zohra Slim, Mizanur Rahman, Rev. Katie Tupling,\r\nChristopher Emmanuel, Abdalrhman Mostafa, Pradeep Eranti, Toby Hodges, Avishkar\r\nBhoopchand, and Carolyn Dickson. We would like to thank our community members and\r\nacknowledge their bravery for sharing their stories that shaped the narrative of these Ten Simple\r\nRules. The stories shared with us formed the case studies, and while they are anonymous\r\nfor privacy and protection reasons, it is these stories that were on our mind during the entire\r\nprocess and kept us going. We acknowledge the efforts of the organisers that contribute to the\r\nhighly successful events that are the inspiration for the ideas presented here: the Deep\r\nLearning Indaba, Neuromatch Academy, the IBRO Simons Computational Neuroscience\r\nImbizo, and OLS. OLS also supported this project through their mentorship programme,\r\nOpen Seeds.","type":"journal_article"},{"month":"07","DOAJ_listed":"1","isi":1,"tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"language":[{"iso":"eng"}],"file":[{"file_id":"18839","creator":"dernst","success":1,"access_level":"open_access","relation":"main_file","date_created":"2025-01-13T10:47:20Z","file_name":"2024_ComprehensivePsychiatry_Beyer.pdf","date_updated":"2025-01-13T10:47:20Z","content_type":"application/pdf","checksum":"aadb57448b5f170761ed72cbcc31ba16","file_size":2874425}],"oa":1,"year":"2024","has_accepted_license":"1","doi":"10.1016/j.comppsych.2024.152479","volume":132,"status":"public","publication_identifier":{"issn":["0010-440X"],"eissn":["1532-8384"]},"type":"journal_article","author":[{"full_name":"Beyer, Chad","first_name":"Chad","last_name":"Beyer"},{"orcid":"0000-0002-4809-5059","first_name":"Christopher","last_name":"Currin","id":"e8321fc5-3091-11eb-8a53-83f309a11ac9","full_name":"Currin, Christopher"},{"first_name":"Taryn","last_name":"Williams","full_name":"Williams, Taryn"},{"last_name":"Stein","first_name":"Dan J.","full_name":"Stein, Dan J."}],"title":"Meta-analysis of the comparative efficacy of benzodiazepines and antidepressants for psychic versus somatic symptoms of generalized anxiety disorder","date_created":"2024-04-07T22:00:55Z","external_id":{"isi":["001221136000001"],"pmid":["38564872"]},"abstract":[{"lang":"eng","text":"Background: Benzodiazepines and antidepressants are effective agents for the treatment of generalized anxiety disorder (GAD), with the HAM-A frequently used as a primary outcome measure. The GAD literature is inconsistent regarding which medications are more effective for somatic versus psychic symptoms of GAD, and treatment guidelines do not advocate for prescribing based on subtype. This meta-analysis aimed to determine whether benzodiazepines and antidepressants have a differential impact on the somatic versus psychic subscales of the HAM-A in GAD.\r\n\r\nMethods: An electronic search was undertaken for randomized controlled trials of either benzodiazepines or antidepressants for GAD that reported treatment response using the HAM-A subscales. Data were extracted by independent reviewers. A random effects assessment of weighted mean difference with 95% confidence intervals and subgroup difference was applied. All analysis was done on SPSS 26. An assessment of bias, and of quality of evidence was performed.\r\n\r\nResults: 24 randomized controlled trials met the inclusion criteria: 18 antidepressant trials, 5 benzodiazepine trials and 1 of both. 14 studies were assessed as having between some and high risk of bias, while 10 were assessed as having low risk of bias. Benzodiazepines (WMD of 1.81 [CI 1.03, 2.58]) were significantly more effective than antidepressants (WMD of 0.83 [CI 0.64, 1.02]) for reducing somatic symptoms of GAD (Chi2 = 5.81, p = 0.02), and were also more effective (WMD of 2.46 [CI 1.83, 3.09]) in reducing psychic symptoms than antidepressants (WMD of 1.83 [CI 1.55, 2.10]), although this comparison did not reach statistical significance (Chi2 = 3.31, p = 0.07).\r\n\r\nConclusion: The finding that benzodiazepines were significantly more effective than antidepressants for somatic symptoms needs to be weighed up against potential benefits of antidepressants over benzodiazepines. It may be useful for future treatment guidelines for GAD to explicitly consider symptom subtype."}],"date_updated":"2025-09-04T13:30:08Z","publication":"Comprehensive Psychiatry","file_date_updated":"2025-01-13T10:47:20Z","pmid":1,"publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_number":"152479","date_published":"2024-07-01T00:00:00Z","OA_type":"gold","ddc":["570"],"citation":{"apa":"Beyer, C., Currin, C., Williams, T., &#38; Stein, D. J. (2024). Meta-analysis of the comparative efficacy of benzodiazepines and antidepressants for psychic versus somatic symptoms of generalized anxiety disorder. <i>Comprehensive Psychiatry</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.comppsych.2024.152479\">https://doi.org/10.1016/j.comppsych.2024.152479</a>","ama":"Beyer C, Currin C, Williams T, Stein DJ. Meta-analysis of the comparative efficacy of benzodiazepines and antidepressants for psychic versus somatic symptoms of generalized anxiety disorder. <i>Comprehensive Psychiatry</i>. 2024;132. doi:<a href=\"https://doi.org/10.1016/j.comppsych.2024.152479\">10.1016/j.comppsych.2024.152479</a>","chicago":"Beyer, Chad, Christopher Currin, Taryn Williams, and Dan J. Stein. “Meta-Analysis of the Comparative Efficacy of Benzodiazepines and Antidepressants for Psychic versus Somatic Symptoms of Generalized Anxiety Disorder.” <i>Comprehensive Psychiatry</i>. Elsevier, 2024. <a href=\"https://doi.org/10.1016/j.comppsych.2024.152479\">https://doi.org/10.1016/j.comppsych.2024.152479</a>.","ista":"Beyer C, Currin C, Williams T, Stein DJ. 2024. Meta-analysis of the comparative efficacy of benzodiazepines and antidepressants for psychic versus somatic symptoms of generalized anxiety disorder. Comprehensive Psychiatry. 132, 152479.","ieee":"C. Beyer, C. Currin, T. Williams, and D. J. Stein, “Meta-analysis of the comparative efficacy of benzodiazepines and antidepressants for psychic versus somatic symptoms of generalized anxiety disorder,” <i>Comprehensive Psychiatry</i>, vol. 132. Elsevier, 2024.","short":"C. Beyer, C. Currin, T. Williams, D.J. Stein, Comprehensive Psychiatry 132 (2024).","mla":"Beyer, Chad, et al. “Meta-Analysis of the Comparative Efficacy of Benzodiazepines and Antidepressants for Psychic versus Somatic Symptoms of Generalized Anxiety Disorder.” <i>Comprehensive Psychiatry</i>, vol. 132, 152479, Elsevier, 2024, doi:<a href=\"https://doi.org/10.1016/j.comppsych.2024.152479\">10.1016/j.comppsych.2024.152479</a>."},"quality_controlled":"1","publisher":"Elsevier","department":[{"_id":"TiVo"}],"intvolume":"       132","scopus_import":"1","article_type":"original","article_processing_charge":"Yes","oa_version":"Published Version","_id":"15295","day":"01"},{"date_updated":"2025-09-08T07:40:58Z","abstract":[{"text":"Memories are thought to be stored in neural ensembles known as engrams that are specifically reactivated during memory recall. Recent studies have found that memory engrams of two events that happened close in time tend to overlap in the hippocampus and the amygdala, and these overlaps have been shown to support memory linking. It has been hypothesized that engram overlaps arise from the mechanisms that regulate memory allocation itself, involving neural excitability, but the exact process remains unclear. Indeed, most theoretical studies focus on synaptic plasticity and little is known about the role of intrinsic plasticity, which could be mediated by neural excitability and serve as a complementary mechanism for forming memory engrams. Here, we developed a rate-based recurrent neural network that includes both synaptic plasticity and neural excitability. We obtained structural and functional overlap of memory engrams for contexts that are presented close in time, consistent with experimental and computational studies. We then investigated the role of excitability in memory allocation at the network level and unveiled competitive mechanisms driven by inhibition. This work suggests mechanisms underlying the role of intrinsic excitability in memory allocation and linking, and yields predictions regarding the formation and the overlap of memory engrams.","lang":"eng"}],"external_id":{"pmid":["38561228"],"isi":["001249681000008"]},"date_created":"2024-06-02T22:00:57Z","author":[{"last_name":"Delamare","first_name":"Geoffroy","full_name":"Delamare, Geoffroy"},{"full_name":"Feitosa Tomé, Douglas","id":"0eed2d40-3d48-11ec-8d38-f789cc2e40b2","first_name":"Douglas","last_name":"Feitosa Tomé"},{"last_name":"Clopath","first_name":"Claudia","full_name":"Clopath, Claudia"}],"title":"Intrinsic neural excitability biases allocation and overlap of memory engrams","date_published":"2024-05-22T00:00:00Z","article_number":"e0846232024","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","pmid":1,"file_date_updated":"2024-06-03T06:34:21Z","publication":"Journal of Neuroscience","publisher":"Society for Neuroscience","quality_controlled":"1","citation":{"ieee":"G. Delamare, D. Feitosa Tomé, and C. Clopath, “Intrinsic neural excitability biases allocation and overlap of memory engrams,” <i>Journal of Neuroscience</i>, vol. 44, no. 21. Society for Neuroscience, 2024.","short":"G. Delamare, D. Feitosa Tomé, C. Clopath, Journal of Neuroscience 44 (2024).","mla":"Delamare, Geoffroy, et al. “Intrinsic Neural Excitability Biases Allocation and Overlap of Memory Engrams.” <i>Journal of Neuroscience</i>, vol. 44, no. 21, e0846232024, Society for Neuroscience, 2024, doi:<a href=\"https://doi.org/10.1523/JNEUROSCI.0846-23.2024\">10.1523/JNEUROSCI.0846-23.2024</a>.","ista":"Delamare G, Feitosa Tomé D, Clopath C. 2024. Intrinsic neural excitability biases allocation and overlap of memory engrams. Journal of Neuroscience. 44(21), e0846232024.","chicago":"Delamare, Geoffroy, Douglas Feitosa Tomé, and Claudia Clopath. “Intrinsic Neural Excitability Biases Allocation and Overlap of Memory Engrams.” <i>Journal of Neuroscience</i>. Society for Neuroscience, 2024. <a href=\"https://doi.org/10.1523/JNEUROSCI.0846-23.2024\">https://doi.org/10.1523/JNEUROSCI.0846-23.2024</a>.","apa":"Delamare, G., Feitosa Tomé, D., &#38; Clopath, C. (2024). Intrinsic neural excitability biases allocation and overlap of memory engrams. <i>Journal of Neuroscience</i>. Society for Neuroscience. <a href=\"https://doi.org/10.1523/JNEUROSCI.0846-23.2024\">https://doi.org/10.1523/JNEUROSCI.0846-23.2024</a>","ama":"Delamare G, Feitosa Tomé D, Clopath C. Intrinsic neural excitability biases allocation and overlap of memory engrams. <i>Journal of Neuroscience</i>. 2024;44(21). doi:<a href=\"https://doi.org/10.1523/JNEUROSCI.0846-23.2024\">10.1523/JNEUROSCI.0846-23.2024</a>"},"ddc":["570"],"day":"22","_id":"17092","article_processing_charge":"Yes (in subscription journal)","oa_version":"Published Version","article_type":"original","scopus_import":"1","intvolume":"        44","department":[{"_id":"TiVo"}],"isi":1,"month":"05","issue":"21","doi":"10.1523/JNEUROSCI.0846-23.2024","has_accepted_license":"1","year":"2024","oa":1,"file":[{"file_id":"17095","success":1,"creator":"dernst","access_level":"open_access","relation":"main_file","date_created":"2024-06-03T06:34:21Z","content_type":"application/pdf","checksum":"4e19159800db605b802c721e4d4b1ffe","file_size":920354,"file_name":"2024_JourNeuroscience_Delamare.pdf","date_updated":"2024-06-03T06:34:21Z"}],"language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"publication_identifier":{"eissn":["1529-2401"],"issn":["0270-6474"]},"status":"public","volume":44,"type":"journal_article","acknowledgement":"We thank Sadra Sadeh and Inês Completo Guerreiro for helpful comments on the manuscript, Yosif Zaki and Denise J. Cai for useful feedback and members of the Clopath lab for discussion and support. This work was supported by Biotechnology and Biological Sciences Research Council (BB/N013956/1 awarded to C.C.), Wellcome Trust (200790/Z/16/Z awarded to C.C.), the Simons Foundation (564408 awarded to C.C.), and Engineering and Physical Sciences Research Council (EP/R035806/1 awarded to C.C.)."},{"status":"public","publication_identifier":{"eissn":["1091-6490"],"issn":["0027-8424"]},"volume":120,"OA_place":"publisher","type":"journal_article","acknowledgement":"We thank Prof. C. Nazaret and Prof. J.-P. Mazat for sharing the code of their mitochondrial model. We also thank G. Miesenböck, E. Marder, L. Abbott, A. Kempf, P. Hasenhuetl, W. Podlaski, F. Zenke, E. Agnes, P. Bozelos, J. Watson, B. Confavreux, and G. Christodoulou, and the rest of the Vogels Lab for their feedback. This work was funded by Wellcome Trust and Royal Society Sir Henry Dale Research Fellowship (WT100000), a Wellcome Trust Senior Research Fellowship (214316/Z/18/Z), and a UK Research and Innovation, Biotechnology and Biological Sciences Research Council grant (UKRI-BBSRC BB/N019512/1).","isi":1,"month":"11","issue":"48","doi":"10.1073/pnas.2306525120","has_accepted_license":"1","related_material":{"link":[{"relation":"software","url":"https://github.com/ccluri/metabolic_spiking"}]},"language":[{"iso":"eng"}],"file":[{"date_updated":"2023-12-11T12:45:12Z","file_name":"2023_PNAS_Chintaluri.pdf","file_size":16891602,"checksum":"bf4ec38602a70dae4338077a5a4d497f","content_type":"application/pdf","relation":"main_file","date_created":"2023-12-11T12:45:12Z","creator":"dernst","success":1,"access_level":"open_access","file_id":"14678"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2023","oa":1,"publisher":"National Academy of Sciences","ddc":["570"],"quality_controlled":"1","citation":{"ama":"Chintaluri C, Vogels TP. Metabolically regulated spiking could serve neuronal energy homeostasis and protect from reactive oxygen species. <i>Proceedings of the National Academy of Sciences of the United States of America</i>. 2023;120(48). doi:<a href=\"https://doi.org/10.1073/pnas.2306525120\">10.1073/pnas.2306525120</a>","apa":"Chintaluri, C., &#38; Vogels, T. P. (2023). Metabolically regulated spiking could serve neuronal energy homeostasis and protect from reactive oxygen species. <i>Proceedings of the National Academy of Sciences of the United States of America</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.2306525120\">https://doi.org/10.1073/pnas.2306525120</a>","chicago":"Chintaluri, Chaitanya, and Tim P Vogels. “Metabolically Regulated Spiking Could Serve Neuronal Energy Homeostasis and Protect from Reactive Oxygen Species.” <i>Proceedings of the National Academy of Sciences of the United States of America</i>. National Academy of Sciences, 2023. <a href=\"https://doi.org/10.1073/pnas.2306525120\">https://doi.org/10.1073/pnas.2306525120</a>.","ista":"Chintaluri C, Vogels TP. 2023. Metabolically regulated spiking could serve neuronal energy homeostasis and protect from reactive oxygen species. Proceedings of the National Academy of Sciences of the United States of America. 120(48), e2306525120.","ieee":"C. Chintaluri and T. P. Vogels, “Metabolically regulated spiking could serve neuronal energy homeostasis and protect from reactive oxygen species,” <i>Proceedings of the National Academy of Sciences of the United States of America</i>, vol. 120, no. 48. National Academy of Sciences, 2023.","mla":"Chintaluri, Chaitanya, and Tim P. Vogels. “Metabolically Regulated Spiking Could Serve Neuronal Energy Homeostasis and Protect from Reactive Oxygen Species.” <i>Proceedings of the National Academy of Sciences of the United States of America</i>, vol. 120, no. 48, e2306525120, National Academy of Sciences, 2023, doi:<a href=\"https://doi.org/10.1073/pnas.2306525120\">10.1073/pnas.2306525120</a>.","short":"C. Chintaluri, T.P. Vogels, Proceedings of the National Academy of Sciences of the United States of America 120 (2023)."},"_id":"14666","article_processing_charge":"Yes (in subscription journal)","oa_version":"Published Version","day":"21","intvolume":"       120","department":[{"_id":"TiVo"}],"article_type":"original","scopus_import":"1","abstract":[{"lang":"eng","text":"So-called spontaneous activity is a central hallmark of most nervous systems. Such non-causal firing is contrary to the tenet of spikes as a means of communication, and its purpose remains unclear. We propose that self-initiated firing can serve as a release valve to protect neurons from the toxic conditions arising in mitochondria from lower-than-baseline energy consumption. To demonstrate the viability of our hypothesis, we built a set of models that incorporate recent experimental results indicating homeostatic control of metabolic products—Adenosine triphosphate (ATP), adenosine diphosphate (ADP), and reactive oxygen species (ROS)—by changes in firing. We explore the relationship of metabolic cost of spiking with its effect on the temporal patterning of spikes and reproduce experimentally observed changes in intrinsic firing in the fruitfly dorsal fan-shaped body neuron in a model with ROS-modulated potassium channels. We also show that metabolic spiking homeostasis can produce indefinitely sustained avalanche dynamics in cortical circuits. Our theory can account for key features of neuronal activity observed in many studies ranging from ion channel function all the way to resting state dynamics. We finish with a set of experimental predictions that would confirm an integrated, crucial role for metabolically regulated spiking and firmly link metabolic homeostasis and neuronal function."}],"date_updated":"2025-09-24T11:16:56Z","external_id":{"isi":["001157389000005"],"pmid":["37988463"]},"date_created":"2023-12-10T23:01:00Z","title":"Metabolically regulated spiking could serve neuronal energy homeostasis and protect from reactive oxygen species","author":[{"full_name":"Chintaluri, Chaitanya","id":"E4EDB536-3485-11EA-98D2-20AF3DDC885E","first_name":"Chaitanya","last_name":"Chintaluri"},{"full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","orcid":"0000-0003-3295-6181","last_name":"Vogels","first_name":"Tim P"}],"project":[{"_id":"c084a126-5a5b-11eb-8a69-d75314a70a87","name":"What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent neuronal networks.","grant_number":"214316/Z/18/Z"}],"article_number":"e2306525120","corr_author":"1","OA_type":"hybrid","date_published":"2023-11-21T00:00:00Z","publication":"Proceedings of the National Academy of Sciences of the United States of America","file_date_updated":"2023-12-11T12:45:12Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","pmid":1,"publication_status":"published"}]